Using Bounded Model Checking for Coverage Analysis of Safety-Critical Software in an Industrial Setting

Testing and Bounded Model Checking (BMC) are two techniques used in Software Verification for bug-hunting. They are expression of two different philosophies: testing is used on the compiled code and it is more suited to find errors in common behaviors, while BMC is used on the source code to find errors in uncommon behaviors of the system. Nowadays, testing is by far the most used technique for software verification in industry: it is easy to use and even when no error is found, it can release a set of tests certifying the (partial) correctness of the compiled system. In the case of safety critical software, in order to increase the confidence of the correctness of the compiled system, it is often required that the provided set of tests covers 100% of the code. This requirement, however, substantially increases the costs associated to the testing phase, since it often involves the manual generation of tests. In this paper we show how BMC can be productively applied to the Software Verification process in industry. In particular, we show how to productively use a Bounded Model Checker for C programs (CBMC) as an automatic test generator for the Coverage Analysis of Safety Critical Software. In particular, we experimented CBMC on a subset of the modules of the European Train Control System (ETCS) of the European Rail Traffic Management System (ERTMS) source code, an industrial system for the control of the traffic railway, provided by Ansaldo STS. The Code of the ERTMS/ETCS, with thousands of lines, has been used as trial application with CBMC obtaining a set of tests satisfying the target 100% code coverage, requested by the CENELEC EN50128 guidelines for software development of safety critical systems. The use of CBMC for test generation led to a dramatic increase in the productivity of the entire Software Development process by substantially reducing the costs of the testing phase. To the best of our knowledge, this is the first time that BMC techniques have been used in an industrial setting for automatically generating tests achieving full coverage of Safety-Critical Software. The positive results demonstrate the maturity of Bounded Model Checking techniques for automatic test generation in industry.     

Identification of Wiener models using optimal local linear models

Identification of a Wiener model using optimal local linear models (LLMs) is presented. The model consists of a discrete-time transfer function and piece-wise linear functions. Parameter estimation as well as partitioning of the LLMs is simultaneously accomplished by the algorithm. The optimality is threefold: first, each local model is linear in the parameters, thus leading to an optimal solution. Second, the model size of each LLM is adaptively optimized using a chi-squared criterion, explicitly incorporating the measurement noise level. Third, the resulting model has a minimum of parameters for a given performance. Simulation results document that the output noise is balanced with the systems nonlinearity.     

Mechanically strong waterborne poly(urethane-urea) films and nanocomposite films

A series of transparent waterborne poly(urethane-urea) (PUU) films and nanocomposite films were prepared using isocyanate excess (5–50 mol% excess relative to the hydroxyl groups) and omitting the common chain-extension step in the acetone method of the preparation. The surplus isocyanate groups were converted into urea and eventually biuret linkages via the reaction with water during the last phase inversion step. Nanocomposites were prepared by the direct mixing of the PUU nanoparticles in water with aqueous nanosilica or montmorillonite powder followed by slow water evaporation. Variable urea/biuret content is responsible for substantially different tensile properties; the neat organic films show elongation-at-break values of 100%–1120%, tensile strength values of 0.07–22.1 MPa, and energy-to-break of 0.1–85 mJ × mm⁻³. All of the materials can be potentially used as soft-to-hard topcoats, depending on the specific demands. The most promising materials are films prepared at 30 and particularly 40 mol% isocyanate excess.     

Telomerase Interaction Partners–Insight from Plants

Telomerase, an essential enzyme that maintains chromosome ends, is important for genome integrity and organism development. Various hypotheses have been proposed in human, ciliate and yeast systems to explain the coordination of telomerase holoenzyme assembly and the timing of telomerase performance at telomeres during DNA replication or repair. However, a general model is still unclear, especially pathways connecting telomerase with proposed non-telomeric functions. To strengthen our understanding of telomerase function during its intracellular life, we report on interactions of several groups of proteins with the Arabidopsis telomerase protein subunit (AtTERT) and/or a component of telomerase holoenzyme, POT1a protein. Among these are the nucleosome assembly proteins (NAP) and the minichromosome maintenance (MCM) system, which reveal new insights into the telomerase interaction network with links to telomere chromatin assembly and replication. A targeted investigation of 176 candidate proteins demonstrated numerous interactions with nucleolar, transport and ribosomal proteins, as well as molecular chaperones, shedding light on interactions during telomerase biogenesis. We further identified protein domains responsible for binding and analyzed the subcellular localization of these interactions. Moreover, additional interaction networks of NAP proteins and the DOMINO1 protein were identified. Our data support an image of functional telomerase contacts with multiprotein complexes including chromatin remodeling and cell differentiation pathways.     

Effect of Type of Protein‐Based Microcapsules and Storage at Various Ambient Temperatures on the Survival and Heat Tolerance of Spray Dried Lactobacillus acidophilus

The aims of this study were to evaluate the effect of types of protein‐based microcapsules and storage at various ambient temperatures on the survival of Lactobacillus acidophilus during exposure to simulated gastrointestinal tract and on the change in thermo‐tolerance during heating treatment. The encapsulating materials were prepared using emulsions of protein (sodium caseinate, soy protein isolate, or pea protein), vegetable oil, and glucose, with maltodextrin was used as a wall material. The formulations were heated at 90 °C for 30 min to develop Maillard substances prior to being incorporated with L. acidophilus. The mixtures were then spray dried. The microspheres were stored at 25, 30, and 35 °C for 8 wk and examined every 4 wk. The addition of proteins as encapsulating materials demonstrated a significant protective effect (P < 0.05) as compared to the control sample. Sodium caseinate and soy protein isolate appeared more effective than pea protein in protecting the bacteria after spray drying and during the storage at different room temperatures. Storage at 35 °C resulted in a significant decrease in survival at end of storage period regardless the type of encapsulating materials. The addition of protein‐based materials also enhanced the survival of L. acidophilus during exposure to simulated gastrointestinal condition as compared to the control. After spray drying and after 0th wk storage, casein, soy protein isolate, and pea protein‐based formulations protected the bacteria during heat treatment. In fact, a significant decrease in thermal tolerance was inevitable after 2 wk of storage at 25 °C.     

Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection

Automated detection and classification of gastric infections (i.e., ulcer, polyp, esophagitis, and bleeding) through wireless capsule endoscopy (WCE) is still a key challenge. Doctors can identify these endoscopic diseases by using the computer‐aided diagnostic (CAD) systems. In this article, a new fully automated system is proposed for the recognition of gastric infections through multi‐type features extraction, fusion, and robust features selection. Five key steps are performed—database creation, handcrafted and convolutional neural network (CNN) deep features extraction, a fusion of extracted features, selection of best features using a genetic algorithm (GA), and recognition. In the features extraction step, discrete cosine transform, discrete wavelet transform strong color feature, and VGG16‐based CNN features are extracted. Later, these features are fused by simple array concatenation and GA is performed through which best features are selected based on K‐Nearest Neighbor fitness function. In the last, best selected features are provided to Ensemble classifier for recognition of gastric diseases. A database is prepared using four datasets—Kvasir, CVC‐ClinicDB, Private, and ETIS‐LaribPolypDB with four types of gastric infections such as ulcer, polyp, esophagitis, and bleeding. Using this database, proposed technique performs better as compared to existing methods and achieves an accuracy of 96.5%.     

Preferential CO oxidation over Pt/3A zeolite catalysts in H2-rich gas for fuel cell application

Even traces of CO in the hydrogen-rich gas fed to proton exchange membrane fuel cells (PEMFC) poison the platinum anode electrode and dramatically decrease the cell power output. In this work, several 1%Pt catalysts, all on 3A-type zeolite support, were prepared starting from different precursors and employing different methods: cation exchange (CE), wet impregnation (WI) and incipient wetness impregnation (IWI). The catalysts were characterised in terms of platinum dispersion and tested under realistic conditions in the quest of a catalyst for the removal of CO via the CO preferential oxidation (CO-PROX) reaction. The best catalytic performance was shown by the 1%Pt–3A catalyst prepared by IWI starting from Pt(NH₃)₄Cl₂ as a precursor, thanks to its highest platinum dispersion.     

Cryo- and xerogel carbon supported PtRu for DMFC anodes

The specific catalytic activity of DMFC anodes based on PtRu may be improved using conducting carbon supports of high surface area and mesoporosity with pore size >20 nm for a high accessible surface area. To this purpose we pursued the strategy of developing PtRu catalysts deposited by chemical and electrochemical route on mesoporous cryo- and xerogel carbons. Here, we report the preparation and characterization data of different mesoporous cryo- and xerogel carbons as well as we present and discuss the results of the structural and morphological study and the catalytic activity data of PtRu catalysts chemically and electrochemically prepared, also by pulse techniques, on such carbons. The results are also compared to those obtained with PtRu supported on the generally used Vulcan carbon support.     

Hybrid Solar Cells from a Blend of Poly(3‐hexylthiophene) and Ligand‐Capped TiO2 Nanorods

Hybrid bulk heterojunction solar cells based on nanocrystalline TiO₂ (nc‐TiO₂) nanorods capped with trioctylphosphine oxide (TOPO) and regioregular poly(3‐hexylthiophene) (P3HT) are processed from solution and characterized in order to relate the device function (optical absorption, charge separation, and transport and photovoltaic properties) to active‐layer properties and device parameters. Annealing the blend films is found to greatly improve the polymer–metal oxide interaction at the nc‐TiO₂/P3HT interface, resulting in a six‐fold increase of the charge separation yield and improved photovoltaic device performance under simulated solar illumination. In addition, the influence of the organic ligand at the nc‐TiO₂ particle surface is found to be crucial for charge separation. Ligand‐exchange procedures applied on the TOPO‐capped nc‐TiO₂ nanorods with an amphiphilic ruthenium‐based dye are found to further improve the charge‐separation yield at the polymer–nanocrystal interface. However, the poor photocurrents generated in the hybrid blend devices, before and after ligand exchange, suggest that transport within or between nanoparticles limits performance. By comparison with other donor–acceptor bulk heterojunction systems, we conclude that charge transport in the nc‐TiO₂:P3HT blend films is limited by the presence of an intrinsic trap distribution mainly associated with the nc‐TiO₂ particles.     

Screening of nucleation conditions using levitated drops for protein crystallization

The growth of suitable protein crystals is an essential step in the structure determination of a protein by X-ray crystallography. At present, crystals are mostly grown using trial-and-error procedures, and protocols that rapidly screen for the crystal nucleation step are rare. Presented here is an approach to minimize the consumption of precious protein material while searching for the nucleation conditions. Acoustically levitated drops of known protein concentration (0.25-1.5-microL volumes) are injected with crystallizing agents using piezoelectric flow-through dispensers (ejecting 50-100-pL droplets at 1-9000 droplets/s). A restricted number of crystallizing agents representing three classes are used: poly(ethylene glycol), salts, and the viscous alcohol 2-methyl 2,4-pentanediol. From a digitized picture of the levitated drop volume, calculations are performed giving the concentrations of all components in the drop at any time during a "precipitation experiment". Supersaturation is the prerequisite for crystal nucleation, and protein precipitation indicates high supersaturation. A light source illuminates the levitated drop, and protein precipitation is monitored using right-angle light scattering. On the basis of these intensity measurements and the volume determination, precipitation diagrams for each crystallizing agent are constructed that give the protein/crystallizing agent concentration boundaries between the minimum and the maximum detectable protein precipitation. Guided by the concentration values obtained from such plots, when approaching the supersaturation region, separate crystallization drops are mixed and allowed to equilibrate under paraffin oil. At conditions in which microcrystals can be observed, the nucleation tendency of the macromolecule is confirmed. Optimization of crystallization conditions can then follow. Proteins tested include alcohol dehydrogenase and D-serine dehydratase. Alcohol dehydrogenase, known to crystallize easily, was used to evaluate whether the ultrasonic field inhibits nucleation. Details are given for the screening procedure of D-serine dehydratase, an enzyme earlier found to be difficult to crystallize reproducibly. The time and material-saving qualities of this method are emphasized, since a range of conditions can quickly be screened using small amounts of protein to roughly determine solubility characteristics of a protein before crystallization trials are initiated.