The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.     

A domain decomposition strategy for alignment of multiple biological sequences on multiprocessor platforms

Multiple Sequences Alignment (MSA) of biological sequences is a fundamental problem in computational biology due to its critical significance in wide ranging applications including haplotype reconstruction, sequence homology, phylogenetic analysis, and prediction of evolutionary origins. The MSA problem is considered NP-hard and known heuristics for the problem do not scale well with increasing numbers of sequences. On the other hand, with the advent of a new breed of fast sequencing techniques it is now possible to generate thousands of sequences very quickly. For rapid sequence analysis, it is therefore desirable to develop fast MSA algorithms that scale well with an increase in the dataset size. In this paper, we present a novel domain decomposition based technique to solve the MSA problem on multiprocessing platforms. The domain decomposition based technique, in addition to yielding better quality, gives enormous advantages in terms of execution time and memory requirements. The proposed strategy allows one to decrease the time complexity of any known heuristic of O(N)^x$O{\left(N\right)}^x$ complexity by a factor of O(1/p)^x$O{(1/p)}^x$, where N$N$ is the number of sequences, x$x$ depends on the underlying heuristic approach, and p$p$ is the number of processing nodes. In particular, we propose a highly scalable algorithm, Sample-Align-D, for aligning biological sequences using Muscle system as the underlying heuristic. The proposed algorithm has been implemented on a cluster of workstations using the MPI library. Experimental results for different problem sizes are analyzed in terms of quality of alignment, execution time and speed-up.     

Synthesis of high molecular weight aromatic polyesters via integrated alternating ring-opening copolymerization and chain extension methods

Due to their good mechanical properties, high molecular weight polyesters (PEs) are highly desirable for a wide range of applications especially in the packaging industry. However, the synthesis of high molecular weight polymers by energy efficient methods is difficult. In this study, a series of semi-aromatic PEs were synthesized via the alternating ring-opening copolymerization (ROCOP) of phthalic anhydride (PA) and cyclohexene oxide (CHO) using a salen chromium(III) complex as a catalyst and 4-(dimethylamino)pyridine as a cocatalyst. By varying the molar ratios between CHO and PA, PEs of different molecular weights were obtained. Hexamethylene diisocyanate was used as a chain extender that further increased the molecular weights of these PEs. These chain extended aromatic polyesters (PE-Xs) showed significant improvement in the glass transition temperature (T_g) values. Thus, integration of ROCOP with the chain extension method can be used as an effective strategy to prepare high molecular weight PEs with improved thermal stabilities and enhanced mechanical properties. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47200.     

Compact Deep Color Features for Remote Sensing Scene Classification

Neural Processing Letters - Aerial scene classification is a challenging problem in understanding high-resolution remote sensing images. Most recent aerial scene classification approaches are based...     

FexCo1−x-doped titanium oxide nanotubes as effective photocatalysts for hydrogen extraction from ammonium phosphate

Theoretically, tri-ammonium phosphate (NH₄)₃PO₄ embeds considerable amount of hydrogen. Typically, the expected hydrogen release from this cheap and stable material is 73.83 mmol/g_salt if a proper catalyst is exploited in the hydrolysis reaction. In this study Fe_xCo_1?x-doped titanium oxide nanotubes are introduced as an efficient photocatalyst under solar radiation. The introduced modified titanium oxide nanotubes have been prepared in two successive steps. First, Na-doped TiO₂ nanotubes were synthesized by hydrothermal treatment in presence of 10 N NaOH solution at 160 °C for 16 h. Then, doping by the proposed metals was carried out by ion exchange process in a microwave oven. X-ray photoelectron microscopy (XPS) and transmission electron microscopy (TEM) confirmed the success of the doping process and the nanotubular morphology, respectively. Study the photo characteristics indicated that the proposed metal doping shifted the band gap from UV to the visible light region as the estimated band gap energies for the as-prepared and doped nanotubes were 3.4 and 2.1 eV, respectively. Moreover, distinct enhancement for the visible light absorption capacity was observed. Accordingly, a distinguished improvement in the photocatalytic activity toward tri-ammonium phosphate hydrolysis was observed. However, the two metals content has a strong influence on the amount of the obtained hydrogen per gram of tri-ammonium phosphate salt. Numerically, the maximum obtained hydrogen was 4.0, 11.2, 11.2, 11.6, 13.4, 16.5, 17.4, 13.4 and 9.8 mmol/g_salt for the pristine TiO₂, and Fe_xCo_1?x-doped TiO₂ with x = 1, 0.8, 0.6, 0.5, 0.4, 0.3, 0.2, and 0.0, respectively.     

Instant Cyclohexene Epoxidation Over Ni-TUD-1 Under Ambient Conditions

Catalysis Letters - To avoid the aggregation problem and activity loss of nickel oxide (NiO) nanoparticles (NPs) in organic reactions, NiO NPs were incorporated into TUD-1 mesoporous material....     

Theranostic Interpolation of Genomic Instability in Breast Cancer

Breast cancer is a diverse disease caused by mutations in multiple genes accompanying epigenetic aberrations of hazardous genes and protein pathways, which distress tumor-suppressor genes and the expression of oncogenes. Alteration in any of the several physiological mechanisms such as cell cycle checkpoints, DNA repair machinery, mitotic checkpoints, and telomere maintenance results in genomic instability. Theranostic has the potential to foretell and estimate therapy response, contributing a valuable opportunity to modify the ongoing treatments and has developed new treatment strategies in a personalized manner. “Omics” technologies play a key role while studying genomic instability in breast cancer, and broadly include various aspects of proteomics, genomics, metabolomics, and tumor grading. Certain computational techniques have been designed to facilitate the early diagnosis of cancer and predict disease-specific therapies, which can produce many effective results. Several diverse tools are used to investigate genomic instability and underlying mechanisms. The current review aimed to explore the genomic landscape, tumor heterogeneity, and possible mechanisms of genomic instability involved in initiating breast cancer. We also discuss the implications of computational biology regarding mutational and pathway analyses, identification of prognostic markers, and the development of strategies for precision medicine. We also review different technologies required for the investigation of genomic instability in breast cancer cells, including recent therapeutic and preventive advances in breast cancer.