An enhanced beam search algorithm for the Shortest Common Supersequence Problem

The Shortest Common Supersequence Problem asks to obtain a shortest string that is a supersequence of every member of a given set of strings. It has applications, among others, in data compression and oligonucleotide microarray production. The problem is NP-hard, and the existing exact solutions are impractical for large instances. In this paper, a new beam search algorithm is proposed for the problem, which employs a probabilistic heuristic and uses the dominance property to further prune the search space. The proposed algorithm is compared with three recent algorithms proposed for the problem on both random and biological sequences, outperforming them all by quickly providing solutions of higher average quality in all the experimental cases. The Java source and binary files of the proposed IBS_SCS algorithm and our implementation of the DR algorithm and all the random and real datasets used in this paper are freely available upon request.     

Predicting Survival Outcomes in the Presence of Unlabeled Data

Many clinical studies require the follow-up of patients over time. This is challenging: apart from frequently observed drop-out, there are often also organizational and financial challenges, which can lead to reduced data collection and, in turn, can complicate subsequent analyses. In contrast, there is often plenty of baseline data available of patients with similar characteristics and background information, e.g., from patients that fall outside the study time window. In this article, we investigate whether we can benefit from the inclusion of such unlabeled data instances to predict accurate survival times. In other words, we introduce a third level of supervision in the context of survival analysis, apart from fully observed and censored instances, we also include unlabeled instances. We propose three approaches to deal with this novel setting and provide an empirical comparison over fifteen real-life clinical and gene expression survival datasets. Our results demonstrate that all approaches are able to increase the predictive performance over independent test data. We also show that integrating the partial supervision provided by censored data in a semi-supervised wrapper approach generally provides the best results, often achieving high improvements, compared to not using unlabeled data.

     

Preparation of novel 2-(2-oxo-2H-chromen-4-yl)-3- arylthiazolidin-4-one derivatives using an efficient ionic liquid catalyst

An eco-friendly procedure for synthesis of 2-(2-oxo-2H-chromen-4-yl)-3-arylthiazolidin-4-one derivatives by three-component reaction of 2-oxo-2H-chromene-4-carbaldehydes, aromatic amines and thioglycolic acid, with tetramethylbutane-1,4-diammonium acetate as a low-cost ionic liquid catalyst under reflux condition is described. The use of an ionic liquid as a catalyst has the advantages of high yields, short reaction time and environmentally friendly reaction media.     

Novel chiral poly(amide-imide)/surface modified SiO2 nanocomposites based on N-trimellitylimido-l-methionine: Synthesis and a morphological study

In the present investigation, novel poly(amide-imide) (PAI)/SiO₂ nanocomposites (NCs) containing l-methionine moiety in the main chain were prepared via a simple and fast ultrasonic irradiation process. PAI was synthesized by direct poly condensation reaction of N-trimellitylimido-l-methionine with 4,4′-diamino diphenylether in molten tetra-n-butyl ammonium bromide/triphenyl phosphite as a green condensing agent. Due to the high surface energy and tendency for agglomeration, the surface of SiO₂ NPs was modified with chiral diacid. The obtained NCs were characterized by Fourier transform-infrared (FT-IR) spectroscopy, thermogravimetry analysis, X-ray powder diffraction, field emission-scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM). The FT-IR spectroscopy indicated that the chiral diacid as the coupling agent was attached on the surface of SiO₂ NPs. FE-SEM, and TEM images showed that SiO₂ NPs were dispersed rather homogeneously in the PAI matrix.     

Channel estimation based on learning automata for OFDM systems

The abundant benefits of Orthogonal Frequency‐Division Multiplexing and its high flexibility have resulted in its widespread applications in many telecommunication standards. One important parameter for improving wireless system's efficiency is the accurate estimation of channel state information. In the literatures, many techniques have been studied in order to estimate the channel state information. Nowadays, the techniques based on intelligent algorithms such as genetic algorithm and particle swarm optimization (PSO) have attracted attention of researchers. With a very low pilot overhead, these techniques are able to estimate the channel frequency response properly only using the received signals. Unfortunately, each of these techniques suffers a common weakness: they have a slow convergence rate. In this paper, a new intelligent and different method has been presented for channel estimation using learning automata, entitled LA estimator, where the learning automata are search agents, and each pair is responsible for searching 1 complex coefficient of the channel frequency response. This method can achieve an accurate channel estimation with a moderate computational complexity in comparison with GA and PSO estimators. Furthermore, with higher convergence rate, our proposed method is capable of providing the same performance as GA and PSO. For a 2‐path fast fading channel, simulation results demonstrate the robustness of our proposed scheme according to the bit error rate and the mean square error.     

Optimum structured adsorbents for gas separation processes

Recent developments in separation technology by adsorption have included the development of new structured adsorbents which offer some attractive characteristics compared to a typical packed bed. These improved features include lower energy consumption, higher throughput and superior recovery and purity of product. However, the exact combination of structural, geometric parameters which yields optimum performance is unknown. This study formulates a methodology for comparison based on a variety of analytical and numerical models and uses it to examine the performance of different adsorbent configurations. In particular, monolithic, laminate and foam structures are evaluated and compared to a packed bed of pellets. The effects of physical adsorbent parameters which govern the performance of a PSA process are considered during model development. Comparisons are carried out based on mass transfer kinetics, adsorbent loading and pressure drop of a PSA system for CO₂/N₂ separation. The results indicated that structured adsorbents can provide superior throughput to packed beds provided their geometrical parameters exceed certain values. For example, laminate structures can offer superior performance to a packed bed of pellets only if the critical sheet thickness and spacing are less than about 0.2 mm. Each adsorbent structure should be designed to operate at its “optimal” velocity. When operating at velocities higher than the “optimal” value, the increase in pressure drop and length of the mass transfer zone more than offsets gains accrued through reduction in cycle time.     

On the hierarchy of conservation laws in a cellular automaton

Conservation laws in cellular automata (CA) are studied as an abstraction of the conservation laws observed in nature. In addition to the usual real-valued conservation laws we also consider more general group-valued and semigroup-valued conservation laws. The (algebraic) conservation laws in a CA form a hierarchy, based on the range of the interactions they take into account. The conservation laws with smaller interaction ranges are the homomorphic images of those with larger interaction ranges, and for each specific range there is a most general law that incorporates all those with that range. For one-dimensional CA, such a most general conservation law has—even in the semigroup-valued case—an effectively constructible finite presentation, while for higher-dimensional CA such effective construction exists only in the group-valued case. It is even undecidable whether a given two-dimensional CA conserves a given semigroup-valued energy assignment. Although the local properties of this hierarchy are tractable in the one-dimensional case, its global properties turn out to be undecidable. In particular, we prove that it is undecidable whether this hierarchy is trivial or unbounded. We point out some interconnections between the structure of this hierarchy and the dynamical properties of the CA. In particular, we show that positively expansive CA do not have non-trivial real-valued conservation laws.     

Effect of interface on mechanical properties and biodegradation of PCL HAp supramolecular nano-composites

This research explores the correlation between the structural properties of supramolecular biocomposites and their mechanical strength. Hybrid biocomposites composed of surface-modified hydroxyapatite nano-particles and supramolecular polycaprolactone (SP PCL), were prepared at different compositions, and their mechanical, thermal and viscoelastic properties as well as biodegradability, biocompatibility and cytotoxicity were evaluated in vitro. The results were compared with those for SP PCL/naked hydroxyapatite nano-composites. We show that surface modification of hydroxyapatite nanoparticles resulted in outstanding improvement of tensile strength and modulus up to 3.6 and 2.2-fold, respectively. At above 10 wt% HAp and 20 wt% HApUPy, heterogeneous nano-composites with inferior mechanical properties were obtained. Based on rheological (in steady shear mode) and small/wide angle X-ray scattering measurements, unusual improved mechanical properties were ascribed to the formation of supramolecular clusters around nanoparticles. In-vitro degradation of the supramolecular nano-composites was also studied to investigate the overall product biodegradation as well as toxicity of the degradation product(s).     

Role of PbSe Structural Stabilization in Photovoltaic Cells

Semiconductor nanocrystals are promising materials for printed optoelectronic devices, but their high surface areas are susceptible to forming defects that hinder charge carrier transport. Furthermore, correlation of chalcogenide nanocrystal (NC) material properties with solar cell operation is not straightforward due to the disorder often induced into NC films during processing. Here, an improvement in long‐range ordering of PbSe NCs symmetry that results from halide surface passivation is described, and the effects on chemical, optical, and photovoltaic device properties are investigated. Notably, this passivation method leads to a nanometer‐scale rearrangement of PbSe NCs during ligand exchange, improving the long‐range ordering of nanocrystal symmetry entirely with inorganic surface chemistry. Solar cells constructed with a variety of architectures show varying improvement and suggest that triplet formation and ionization, rather than carrier transport, is the limiting factor in singlet fission solar cells. Compared to existing protocols, our synthesis leads to PbSe nanocrystals with surface‐bound chloride ions, reduced sub‐bandgap absorption and robust materials and devices that retain performance characteristics many hours longer than their unpassivated counterparts.     

Qualitative analysis of ganoderic acids in Ganoderma lucidum from Iran and China by RP-HPLC and electrospray ionisation-mass spectrometry (ESI-MS)

Ganoderma lucidum is used as a health food and medicine in Far East and produces different ganoderic acids which are well known for their valuable bioactivities. In this study, two different strains of G. lucidum from Iran and China were investigated for ganoderic acids, using reversed phase HPLC (RP-HPLC) in combination with UV and electrospray ionisation-mass spectrometry (ESI-MS). The results showed a relatively low intensity ganoderic acid C2 peak in the chromatogram of the Iranian sample. However, three high intensity peaks attributed to the well known ganoderic acids including ganoderic acids T, Me and H from the Chinese strain. These findings clearly indicated that different strains of G. lucidum could posses a range of active compounds and hence, bioactivities. Moreover, the variation in the triterpenoid components encourages more studies on the rest of bioactive molecules, and also different strains grown in a variety of climatic and geographical conditions.