Learning a Static Analyzer from Data

To be practically useful, modern static analyzers must precisely model the effect of both, statements in the programming language as well as frameworks used by the program under analysis. While important, manually addressing these challenges is difficult for at least two reasons: (i) the effects on the overall analysis can be non-trivial, and (ii) as the size and complexity of modern libraries increase, so is the number of cases the analysis must handle. In this paper we present a new, automated approach for creating static analyzers: instead of manually providing the various inference rules of the analyzer, the key idea is to learn these rules from a dataset of programs. Our method consists of two ingredients: (i) a synthesis algorithm capable of learning a candidate analyzer from a given dataset, and (ii) a counter-example guided learning procedure which generates new programs beyond those in the initial dataset, critical for discovering corner cases and ensuring the learned analysis generalizes to unseen programs. We implemented and instantiated our approach to the task of learning JavaScript static analysis rules for a subset of points-to analysis and for allocation sites analysis. These are challenging yet important problems that have received significant research attention. We show that our approach is effective: our system automatically discovered practical and useful inference rules for many cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned analyzers

Formal Verification of Neural Network Controlled Autonomous Systems

In this paper, we consider the problem of formally verifying the safety of an autonomous robot equipped with a Neural Network (NN) controller that processes LiDAR images to produce control actions. Given a workspace that is characterized by a set of polytopic obstacles, our objective is to compute the set of safe initial conditions such that a robot trajectory starting from these initial conditions is guaranteed to avoid the obstacles. Our approach is to construct a finite state abstraction of the system and use standard reachability analysis over the finite state abstraction to compute the set of the safe initial states. The first technical problem in computing the finite state abstraction is to mathematically model the imaging function that maps the robot position to the LiDAR image. To that end, we introduce the notion of imaging-adapted sets as partitions of the workspace in which the imaging function is guaranteed to be affine. We develop a polynomial-time algorithm to partition the workspace into imaging-adapted sets along with computing the corresponding affine imaging functions. Given this workspace partitioning, a discrete-time linear dynamics of the robot, and a pre-trained NN controller with Rectified Linear Unit (ReLU) nonlinearity, the second technical challenge is to analyze the behavior of the neural network. To that end, we utilize a Satisfiability Modulo Convex (SMC) encoding to enumerate all the possible segments of different ReLUs. SMC solvers then use a Boolean satisfiability solver and a convex programming solver and decompose the problem into smaller subproblems. To accelerate this process, we develop a pre-processing algorithm that could rapidly prune the space feasible ReLU segments. Finally, we demonstrate the efficiency of the proposed algorithms using numerical simulations with increasing complexity of the neural network controller

Suggestions for improving the design of clinical trials in multiple sclerosis - results of a systematic analysis of completed phase III trials

This manuscript reviews the primary and secondary endpoints of pivotal phase III trials with immunomodulatory drugs in multiple sclerosis (MS). Considering the limitations of previous trial designs, we propose new standards for the planning of clinical trials, taking into account latest insights into MS pathophysiology and patient-relevant aspects. Using a systematic overview of published phase III (pivotal) trials performed as part of application for drug market approval, we evaluate the following characteristics: trial duration, number of trial participants, comparators, and endpoints (primary, secondary, magnetic resonance imaging outcome, and patient-reported outcomes). From a patient perspective, the primary and secondary endpoints of clinical trials are only partially relevant. High-quality trial data pertaining to efficacy and safety that stretch beyond the time frame of pivotal trials are almost non-existent. Understanding of long-term benefits and risks of disease-modifying MS therapy is largely lacking. Concrete proposals for the trial designs of relapsing (remitting) multiple sclerosis/clinically isolated syndrome, primary progressive multiple sclerosis, and secondary progressive multiple sclerosis (e.g., study duration, mechanism of action, and choice of endpoints) are presented based on the results of the systematic overview. Given the increasing number of available immunotherapies, the therapeutic strategy in MS has shifted from a mere "relapse-prevention" approach to a personalized provision of medical care as to the choice of the appropriate drugs and their sequential application over the course of the disease. This personalized provision takes patient preferences as well as disease-related factors into consideration such as objective clinical and radiographic findings but also very burdensome symptoms such as fatigue, depression, and cognitive impairment. Future trial designs in MS will have to assign higher relevance to these patient-reported outcomes and will also have to implement surrogate measures that can serve as predictive markers for individual treatment response to new and investigational immunotherapies. This is an indispensable prerequisite to maximize the benefit of individual patients when participating in clinical trials. Moreover, such appropriate trial designs and suitable enrolment criteria that correspond to the mode of action of the study drug will facilitate targeted prevention of adverse events, thus mitigating risks for individual study participants

Calcaneal nonunion: three cases and a review of the literature

The long-term follow-up of intra-articular calcaneal fractures is often accompanied by complications. Frequently occurring are arthrosis, arthrofibrosis of the subtalar joint, and malunion. Uncommon is the calcaneal nonunion. A total of three cases is presented in this report, including a review of the literature. The occurrence of a nonunion appears to be more common after conservative treatment, but the pathophysiology remains unclear, however smoking may play a role

Strong Interactions of Single Atoms and Photons near a Dielectric Boundary

Modern research in optical physics has achieved quantum control of strong interactions between a single atom and one photon within the setting of cavity quantum electrodynamics (cQED). However, to move beyond current proof-of-principle experiments involving one or two conventional optical cavities to more complex scalable systems that employ N >> 1 microscopic resonators requires the localization of individual atoms on distance scales < 100 nm from a resonator's surface. In this regime an atom can be strongly coupled to a single intracavity photon while at the same time experiencing significant radiative interactions with the dielectric boundaries of the resonator. Here, we report an initial step into this new regime of cQED by way of real-time detection and high-bandwidth feedback to select and monitor single Cesium atoms localized ~100 nm from the surface of a micro-toroidal optical resonator. We employ strong radiative interactions of atom and cavity field to probe atomic motion through the evanescent field of the resonator. Direct temporal and spectral measurements reveal both the significant role of Casimir-Polder attraction and the manifestly quantum nature of the atom-cavity dynamics. Our work sets the stage for trapping atoms near micro- and nano-scopic optical resonators for applications in quantum information science, including the creation of scalable quantum networks composed of many atom-cavity systems that coherently interact via coherent exchanges of single photons.Comment: 8 pages, 5 figures, Supplemental Information included as ancillary fil

Quantum computing implementations with neutral particles

We review quantum information processing with cold neutral particles, that is, atoms or polar molecules. First, we analyze the best suited degrees of freedom of these particles for storing quantum information, and then we discuss both single- and two-qubit gate implementations. We focus our discussion mainly on collisional quantum gates, which are best suited for atom-chip-like devices, as well as on gate proposals conceived for optical lattices. Additionally, we analyze schemes both for cold atoms confined in optical cavities and hybrid approaches to entanglement generation, and we show how optimal control theory might be a powerful tool to enhance the speed up of the gate operations as well as to achieve high fidelities required for fault tolerant quantum computation.Comment: 19 pages, 12 figures; From the issue entitled "Special Issue on Neutral Particles

Urine disinfection and in situ pathogen killing using a Microbial Fuel Cell cascade system

© 2017 Ieropoulos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Microbial Fuel Cells (MFCs) are emerging as an effective means of treating different types of waste including urine and wastewater. However, the fate of pathogens in an MFC-based system remains unknown, and in this study we investigated the effect of introducing the enteric pathogen Salmonella enterica serovar enteritidis in an MFC cascade system. The MFCs continuously fed with urine showed high disinfecting potential. As part of two independent trials, during which the bioluminescent S. enteritidis strain was introduced into the MFC cascade, the number of viable counts and the level of bioluminescence were reduced by up to 4.43-0.04 and 4.21-0.01 log-fold, respectively. The killing efficacy observed for the MFCs operating under closed-circuit conditions, were higher by 1.69 and 1.72 log-fold reduction than for the open circuit MFCs, in both independent trials. The results indicated that the bactericidal properties of a well performing anode were dependent on power performance and the oxidation-reduction potential recorded for the MFCs. This is the first time that the fate of pathogenic bacteria has been investigated in continuously operating MFC systems

Mucociliary and long-term particle clearance in airways of patients with immotile cilia

Spherical monodisperse ferromagnetic iron oxide particles of 1.9 μm geometric and 4.2 μm aerodynamic diameter were inhaled by seven patients with primary ciliary dyskinesia (PCD) using the shallow bolus technique, and compared to 13 healthy non-smokers (NS) from a previous study. The bolus penetration front depth was limiting to the phase1 dead space volume. In PCD patients deposition was 58+/-8 % after 8 s breath holding time. Particle retention was measured by the magnetopneumographic method over a period of nine months. Particle clearance from the airways showed a fast and a slow phase. In PCD patients airway clearance was retarded and prolonged, 42+/-12 % followed the fast phase with a mean half time of 16.8+/-8.6 hours. The remaining fraction was cleared slowly with a half time of 121+/-25 days. In healthy NS 49+/-9 % of particles were cleared in the fast phase with a mean half time of 3.0+/-1.6 hours, characteristic of an intact mucociliary clearance. There was no difference in the slow clearance phase between PCD patients and healthy NS. Despite non-functioning cilia the effectiveness of airway clearance in PCD patients is comparable to healthy NS, with a prolonged kinetics of one week, which may primarily reflect the effectiveness of cough clearance. This prolonged airway clearance allows longer residence times of bacteria and viruses in the airways and may be one reason for increased frequency of infections in PCD patients

The fading of reported effectiveness. A meta-analysis of randomised controlled trials

BACKGROUND: The "real" effect size of a medical therapy is constant over time. In contrast, the effect size reported in randomised controlled trials (RCTs) may change over time because the sum of all kinds of bias influencing the reported effectiveness is not necessarily constant. As this would affect the validity of meta-analyses, we tested the hypothesis that the reported effect size decreases over time. Furthermore, we tested three hypotheses that would explain a possible change. METHODS: Because of well established outcome measures, the lipid-lowering drugs Pravastatin and Atorvastatin (serum low-density lipoprotein cholesterol, LDL-C) and the anti-glaucoma drugs Timolol and Latanoprost (intraocular pressure, IOP) were chosen for this investigation. Studies were identified by a standardized MEDLINE search. RCTs investigating the above identified medications administered as monotherapy, and in defined dosages, were included. Publication year, baseline (= pre-treatment value in the treatment group of interest) and post intervention means, number of patients and the assignment to experimental or control group were extracted for each study. RESULTS: A total of 625 citations were screened; 206 met the inclusion criteria. The reported effect size of Pravastatin (change of reported effect size in five years: -3.22% LDL-C, P < .0001), Timolol (-0.56 mmHg, P < .0001) and Latanoprost (-1.78 mmHg, P = .0074) decreased over time, while there was no significant change for Atorvastatin (+0.31% LDL-C, P = .8618). Multiple regression analysis showed that baseline values were the most important influencing factor; study size or treatment group did not play a significant role. CONCLUSION: The effectiveness of medical therapies reported in RCTs decreases over time in three of the four investigated pharmaceuticals, caused mainly by baseline differences. We call this phenomenon "fading of reported effectiveness". Under this condition the validity of a meta-analysis may be impaired. Therefore we propose to observe this phenomenon in future meta-analyses in order to guarantee a maximum of transparency

Surfactant protein B gene variations enhance susceptibility to squamous cell carcinoma of the lung in German patients

Genetic factors are thought to influence the risk for lung cancer. Since pulmonary surfactant mediates the response to inhaled carcinogenic substances, candidate genes may be among those coding for pulmonary surfactant proteins. In the present matched case–control study a polymorphism within intron 4 of the gene coding for surfactant specific protein B was analysed in 357 individuals. They were divided into 117 patients with lung cancer (40 patients with small cell lung cancer, 77 patients with non small cell lung cancer), matched controls and 123 healthy individuals. Surfactant protein B gene variants were analysed using specific PCR and cloned surfactant protein B sequences as controls. The frequency of the intron 4 variation was similar in both control groups (13.0% and 9.4%), whereas it was increased in the small cell lung cancer group (17.5%) and the non small cell lung cancer group (16.9%). The gene variation was found significantly more frequently in patients with squamous cell carcinoma (25.0%, P=0.016, odds ratio=3.2, 95%CI=1.24–8.28) than in the controls. These results indicate an association of the surfactant protein B intron 4 variants and/or its flanking loci with mechanisms that may enhance lung cancer susceptibility, especially to squamous cell carcinoma of the lung