Cost-Efficient Scheduling for Deadline Constrained Grid Workflows

Cost optimization for workflow scheduling while meeting deadline is one of the fundamental problems in utility computing. In this paper, a two-phase cost-efficient scheduling algorithm called critical chain is presented. The proposed algorithm uses the concept of slack time in both phases. The first phase is deadline distribution over all tasks existing in the workflow which is done considering critical path properties of workflow graphs. Critical chain uses slack time to iteratively select most critical sequence of tasks and then assigns sub-deadlines to those tasks. In the second phase named mapping step, it tries to allocate a server to each task considering task's sub-deadline. In the mapping step, slack time priority in selecting ready task is used to reduce deadline violation. Furthermore, the algorithm tries to locally optimize the computation and communication costs of sequential tasks exploiting dynamic programming. After proposing the scheduling algorithm, three measures for the superiority of a scheduling algorithm are introduced, and the proposed algorithm is compared with other existing algorithms considering the measures. Results obtained from simulating various systems show that the proposed algorithm outperforms four well-known existing workflow scheduling algorithms

Malaysia’s Agricultural Production Dropped and the Impact of Climate Change: Applying and Extending the Theory of Cobb Douglas Production

Under climate change, Malaysia's agricultural production showed decreasing in recent decades. This study tries to fill in the gaps to applying and extending the Cobb Douglas production function theory to examine the impact of climate change and economic factors on Malaysia's agricultural production. Using Engle-Granger (EG) test with 37 years of data from 1980 to 2016. The findings showed that the long-run estimated coefficients for rainfall, temperature, and interest rate were -0.338, -0.024, and -0.029, respectively. This indicates that each additional percent in rainfall, temperature, and interest rate will be affected the agricultural production, on average, to decrease by 0.338%, 0.024%, and 0.029%, respectively, holding others constant. Besides that, the long-run elasticity of real GDP per capita, employment, and Trend showed 0.509, 0.513, and 0.119, respectively. Increase 1% of real GDP per capita will lead to the agricultural production to increase about 0.509%, ceteris paribus. The elasticity of employment showed that each 10% increase in agricultural employment will increase the agricultural production on average 5.13%, ceteris paribus. Furthermore, the trend estimated coefficient showed that the agricultural production will have a constant growth rate which is 0.119% per year. All variables were statistically significant to explain the long-run agricultural production. The short-run rainfall, temperature, employment, and Trend were statistically significant to determine the short-run production growth. Therefore, advanced technology and the latest information on climate change are relevant to boost agricultural production growth. In addition, policymakers also suggested establishing lower interest rate loan facilities and no labor shortage in this industry

An experimental and numerical study of the microstructural and biomechanical properties of human peripheral nerve endoneurium for the design of tissue scaffolds

Biomimetic design of scaffold architectures represents a promising strategy to enable the repair of tissue defects. Natural endoneurium extracellular matrix (eECM) exhibits a sophisticated microstructure and remarkable microenvironments conducive for guiding neurite regeneration. Therefore, the analysis of eECM is helpful to the design of bionic scaffold. Unfortunately, a fundamental lack of understanding of the microstructural characteristics and biomechanical properties of the human peripheral nerve eECM exists. In this study, we used microscopic computed tomography (micro-CT) to reconstruct a three-dimensional (3D) eECM model sourced from mixed nerves. The tensile strength and effective modulus of human fresh nerve fascicles were characterized experimentally. Permeability was calculated from a computational fluid dynamic (CFD) simulation of the 3D eECM model. Fluid flow of acellular nerve fascicles was tested experimentally to validate the permeability results obtained from CFD simulations. The key microstructural parameters, such as porosity is 35.5 ± 1.7%, tortuosity in endoneurium (X axis is 1.26 ± 0.028, Y axis is 1.26 ± 0.020 and Z axis is 1.17 ± 0.03, respectively), tortuosity in pore (X axis is 1.50 ± 0.09, Y axis is 1.44 ± 0.06 and Z axis is 1.13 ± 0.04, respectively), surface area-to-volume ratio (SAVR) is 0.165 ± 0.007 μm−1 and pore size is 11.8 ± 2.8 μm, respectively. These were characterized from the 3D eECM model and may exert different effects on the stiffness and permeability. The 3D microstructure of natural peripheral nerve eECM exhibits relatively lower permeability (3.10 m2 × 10−12 m2) than other soft tissues. These key microstructural and biomechanical parameters may play an important role in the design and fabrication of intraluminal guidance scaffolds to replace natural eECM. Our findings can aid the development of regenerative therapies and help improve scaffold design

A Fault Tolerant Scheduling Algorithm for DAG Applications in Cluster Environments.

Abstract. Fault tolerance is an essential requirement in systems running applications which need a technique to continue execution where some system components are subject to failure. In this paper, a fault tolerant task scheduling algorithm is proposed for mapping task graphs to heterogeneous processing nodes in cluster computing systems. The starting point of the algorithm is a DAG representing an application with information about the tasks. This information consists of the execution time of the tasks on the target system processors, communication times between the tasks having data dependencies, and the number of the processor failures (ε) which should be tolerated by the scheduling algorithm. The algorithm is based on the active replication scheme, and it schedules ε+1 replicas of each task to achieve the required fault tolerance. Simulation results show the efficiency of the proposed algorithm in spite of its lower complexity

Investigation of Underground Gas Storage in a Partially Depleted Naturally Fractured Gas Reservoir

ABSTRACT: In this work, studies of underground gas storage (UGS) were performed on a partially depleted, naturally fractured ga

Engineering of 2D nanomaterials to trap and kill SARS-CoV-2 : a new insight from multi-microsecond atomistic simulations

In late 2019, coronavirus disease 2019 (COVID-19) was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Spike protein is one of the surface proteins of SARS-CoV-2 that is essential for its infectious function. Therefore, it received lots of attention for the preparation of antiviral drugs, vaccines, and diagnostic tools. In the current study, we use computational methods of chemistry and biology to study the interaction between spike protein and its receptor in the body, angiotensin-I-converting enzyme-2 (ACE2). Additionally, the possible interaction of two-dimensional (2D) nanomaterials, including graphene, bismuthene, phosphorene, p-doped graphene, and functionalized p-doped graphene, with spike protein is investigated. The functionalized p-doped graphene nanomaterials were found to interfere with spike protein better than the other tested nanomaterials. In addition, the interaction of the proposed nanomaterials with the main protease (M-pro) of SARS-CoV-2 was studied. Functionalized p-doped graphene nanomaterials showed more capacity to prevent the activity of M-pro. These 2D nanomaterials efficiently reduce the transmissibility and infectivity of SARS-CoV-2 by both the deformation of the spike protein and inhibiting the M-pro. The results suggest the potential use of 2D nanomaterials in a variety of prophylactic approaches, such as masks or surface coatings, and would deserve further studies in the coming years.Peer reviewe

Correlation between caries prevalence and chronic perodontitis

Introduction: Periodontitis and dental caries may be synergistically associated, negatively associated, or completely independent. The aim of this study was to evaluate the correlation between these two diseases and investigate the prevalence of dental caries in periodontitis. Methods: This cross-sectional study has been performed in 180 samplesin two groups: periodontal and control group; during 2012-2013 in Babol Dental School. All 180 patients were divided into two groups, including 90 cases with chronic periodontitis as the periodontal group (PG) and 90 cases with healthy gums as the control group (probing depth between 2-3mm) (HG). Clinical measurments in cluding Gingival Index (GI), Bleeding Index ( BI), Clinical Attachment Loss (CAL), Periodontal Pocket Depth (PPD) were used to assess the severity of periodontal disease. The clinical features of control group were healthy gums, probing less than 3mm in depth, and CAL<1mm. The examination to measure AL was conducted using a Williams’s periodontal probe. In chronic periodontitis group, the patients had GI≥1 and CAL≥1. The assessment of caries of patients was conducted using bitewing radiography for proximal caries detection, dent on the use of explorer and direct observation. A p-value≤0.05 is considered as significant. Results: The results of this study showed that the mean number of decayed and filled teeth (DFT) in periodontal group was 4.32±0.17, and in healthy group was 2.16±0.17. DFT in males with periodontitis was 4.85±0.17 and in females was 4.3±0.17,while the healthy males was 2.54±0.17, and females was 2.25±0.17; therefore, the mean DFT in the periodontal group was more than the healthy group (p≤0.05). Conclusion: Based on our findings, in patients with periodontitis, more dental carries were more significant than the healthy group

Evaluation of the efficacy of Niosomal Curcumin Nanoformulation in Cancer therapy

During the past decade vesicles as a tool to improve drug delivery, has created a lot of interest amongst the scientist working in the area of drug delivery systems. Based on their biodegradable, biocompatible and nonimmunogenic structure, niosomes are promising drug carriers that are formed by self-assembly of nonionic surfactants and cholesterol in an aqueous phase. Curcumin (Cur),  a natural polyphenol found in Curcuma longa, has been utilized in multiple medicinal areas from antibiotic to antitumor treatment. However, the chemical structure of curcumin results in poor stability, low solubility and rapid degradation in vivo, limiting its clinical utilization. To address these problems, we have prepared a niosome system composed of nonionic surfactants polyoxyethylene sorbitan monostearate and cholesterol by thin film hydration method. The niosomal curcumin was evaluated for anti-cancer efficacy in prostate cancer cell line (PC-3) by MTT assay. Cur was encapsulated in the niosomes with a high entrapment efficiency of 98.4 ± 0.4%. Average particle size was found to be 127.5 ± 1.2 nm. Niosomal curcumin (Nio -Cur)  exhibited enhanced cytotoxic activity against PC-3 cells compared with free Cur. These results demonstrated that the Nio -Cur system is a promising strategy for the delivery of Cur and prostate cancer therapy.

A novel Paclitaxel loaded Noisome: Preparation, Characterization and Cytotoxicity Assessment against human prostate cancer

Prostate cancer (PCa) is one of the most common cancers and the second leading cause of cancer death in men.  Regarding that prostate cancer is the most common form of cancer in men and is the second leading cause of cancer mortality, paclitaxel, as a chemotherapeutic agent with a wide spectrum of antitumor activity, could be utilized in treatment of this malignancy. Paclitaxel side effects are severe hypersensitivity reactions, neurotoxicity, and nephrotoxicity. Today’s decline of side effects and increase in efficacy of chemotherapeutic agents by applying nanotechnology in medicine is the target of scientists. Niosomes or nonionic surfactant vesicles are nano vehicles utilized in drug delivery systems. Niosomes are prepared by various methods. Our present work investigated the efficiency of encapsulation of paclitaxel in noisome (Nio-PTX) as a novel vesicular drug delivery system and cytotoxic effects on PC-3 prostate cancer cell line. In this study, paclitaxel loaded niosome was prepared by thin film hydration method. The characterization tests that included dynamic light scattering (DLS) and UV-Vis spectrophotometry were employed to evaluate the quality of the nanocarriers. Percent of encapsulation paclitaxel prepared with sorbitane monostearate and cholesterol was 99.4%. In addition, the polydispersity index, mean size diameter and zeta potentials of niosomal paclitaxel nanoparticles were found to be 0.203 ± 0.012, 119.7 ± 2.5 nm and -4 ± 0.34, respectively. Cytotoxicity of niosomal paclitaxel nanoparticles and free paclitaxel on human prostate cancer cell line PC-3 after 24 hours were studied by MTT assay to determine cell viability. The results demonstrated that a 1.5∼fold reduction in paclitaxel concentration was measured when the paclitaxel administered in nanoniosome compared to free paclitaxel solution in PC3 human prostate cancer cell line. As a result, the nanoparticle-based formulation of paclitaxel has high potential as an adjuvant therapy for clinical usage in human prostate cancer therapy