SLDG: a metamodel for Simulink/Stateflow models and its applications

Simulink and Stateflow (SL/SF) models are being widely used to design and develop embedded systems. Often the SL/SF models of embedded controllers turn out to be large and consist of many subsystems and hierarchies. When such a system is maintained, it becomes difficult to manually analyse the model to identify the impacted elements due to the existence of several explicit and implicit dependencies among the model elements. To automate the analysis of an SL/SF model, we propose a metamodel to capture various types of dependencies existing across the basic blocks. We have named this metamodel Simulink dependency graph (SLDG). We investigate the use of SLDG in change impact visualization and regression test selection. We have developed a prototype tool by implementing our approach for the aforementioned applications.     

3D Printing technologies for drug delivery: a review

With the FDA approval of the first 3D printed tablet, Spritam®, there is now precedence set for the utilization of 3D printing for the preparation of drug delivery systems. The capabilities for dispensing low volumes with accuracy, precise spatial control and layer-by-layer assembly allow for the preparation of complex compositions and geometries. The high degree of flexibility and control with 3D printing enables the preparation of dosage forms with multiple active pharmaceutical ingredients with complex and tailored release profiles. A unique opportunity for this technology for the preparation of personalized doses to address individual patient needs. This review will highlight the 3D printing technologies being utilized for the fabrication of drug delivery systems, as well as the formulation and processing parameters for consideration. This article will also summarize the range of dosage forms that have been prepared using these technologies, specifically over the last 10 years.     

Two minimum spanning forest algorithms on fixed-size hypercube computers

Two parallel algorithms for finding minimum spanning forest (MSF) of a weighted undirected graph on hypercube computers, consisting of a fixed number of processors, are presented. One algorithm is suited for sparse graphs, the other for dense graphs. Our design strategy is based on successive elimination of non-MSF edges. The input graph is partitioned equally among different processors, which then repeatedly eliminate non-MSF edges and merge results to gradually construct the desired MSF of the entire graph. Low communication overhead is achieved by restricting the message-flow to between the neighboring processors in the hypercube topology. The correctness of our approach is due to a theorem which states that with total-ordered edges, if an edge of an arbitrary subgraph does not belong to its MSF, then it does not belong to the MSF of the entire graph. For a graph of n vertices and m edges, our first algorithm finds an MSF in O(m log m)/p) time using p processors for p ≤ (mlog m)/n(1+log(m/n)). The second algorithm, efficient for dense graphs, requires O(n²/p) time for p≤n/log n.     

A survey of recent advances in SAT-based formal verification

Dramatic improvements in SAT solver technology over the last decade and the growing need for more efficient and scalable verification solutions have fueled research in verification methods based on SAT solvers. This paper presents a survey of the latest developments in SAT-based formal verification, including incomplete methods such as bounded model checking and complete methods for model checking. We focus on how the surveyed techniques formulate the verification problem as a SAT problem and how they exploit crucial aspects of a SAT solver, such as application-specific heuristics and conflict-driven learning. Finally, we summarize the noteworthy achievements in this area so far and note the major challenges in making this technology more pervasive in industrial design verification flows.     

Inter-relationships among the properties of fatty oils

Properties of fatty oils, such as viscosity (η), iodine value (IV) and saponification value (SV), are useful in the design of methods and equipments for the processing of the fatty oils to value-added products. This investigation is aimed at the development of generalized empirical relationships based on a model similar to the Antoine equation for vapor pressure. Two equations resulted. The first equation: log η = [−1.4 + 1.25 (IV/SV)] + [500 − 375 (IV/SV)]/ [(t + 140) − 85 (IV/SV)] relating the logarithm of viscosity to the ratio of iodine value to saponification value (IV/SV) and temperature in degrees centigrade (t), gives an average absolute deviation of 13.0% at 77 data points of several fatty oils. The second equation, somewhat simpler in form: log η = −0.6298 + [273.66/ (t + 88.81) ] relating the logarithm of viscosity directly to the temperature in degrees centigrade (t), gives an average absolute deviation of 14.5% at 89 data points of a larger group of fatty oils ranging from almond to tallow. The two equations can be used conveniently to predict either viscosity, iodine value or saponification value, when the other two properties are known, for design purposes.     

High throughput multiscale modeling for design of experiments,catalysts, and reactors: Application to hydrogen production from ammonia

A novel approach for design of experiments (DOE) is outlined that combines high throughput multiscale modeling, sensitivity analysis, and information extraction from massive computational data using informatics tools. This approach is implemented by conducting experiments of ammonia decomposition on a Ru/γ-Al₂O₃ catalyst in a fixed bed reactor. It is shown that a relatively small number of experiments chosen from this new DOE approach can enable refinement of microkinetic models and render them predictive over the (large) experimentally important parameter space. Microkinetic models are subsequently used for process and product design. Specifically, a membrane fixed bed reactor is simulated and is shown to outperform the conventional fixed bed reactor at intermediate temperatures for hydrogen production. Also, the attributes of the best catalyst for ammonia decomposition are identified as a function of processing conditions. It is shown that for NH₃ decomposition, processing conditions do not significantly affect the best catalyst choice. In contrast, fundamental physicochemical phenomena, such as adsorbate–adsorbate interactions, can have a profound effect on catalyst discovery.