Search

Massive computation power and storage capacity of cloud computing systems allow scientists to deploy computation and data intensive applications without infrastructure investment, where large application data sets can be stored in the cloud. Based on the pay-as-you-go model, storage strategies and benchmarking approaches have been developed for cost-effectively storing large volume of generated application data sets in the cloud. However, they are either insufficiently cost-effective for the storage or impractical to be used at runtime. In this paper, toward achieving the minimum cost benchmark, we propose a novel highly cost-effective and practical storage strategy that can automatically decide whether a generated data set should be stored or not at runtime in the cloud. The main focus of this strategy is the local-optimization for the tradeoff between computation and storage, while secondarily also taking users' (optional) preferences on storage into consideration. Both theoretical analysis and simulations conducted on general (random) data sets as well as specific real world applications with Amazon's cost model show that the cost-effectiveness of our strategy is close to or even the same as the minimum cost benchmark, and the efficiency is very high for practical runtime utilization in the cloud. [ABSTRACT FROM AUTHOR]

Cloud computing provides massive computation power and storage capacity which enable users to deploy computation and data-intensive applications without infrastructure investment. Along the processing of such applications, a large volume of intermediate data sets will be generated, and often stored to save the cost of recomputing them. However, preserving the privacy of intermediate data sets becomes a challenging problem because adversaries may recover privacy-sensitive information by analyzing multiple intermediate data sets. Encrypting ALL data sets in cloud is widely adopted in existing approaches to address this challenge. But we argue that encrypting all intermediate data sets are neither efficient nor cost-effective because it is very time consuming and costly for data-intensive applications to en/decrypt data sets frequently while performing any operation on them. In this paper, we propose a novel upper bound privacy leakage constraint-based approach to identify which intermediate data sets need to be encrypted and which do not, so that privacy-preserving cost can be saved while the privacy requirements of data holders can still be satisfied. Evaluation results demonstrate that the privacy-preserving cost of intermediate data sets can be significantly reduced with our approach over existing ones where all data sets are encrypted. [ABSTRACT FROM AUTHOR]

Studies on the effect of CrylAb protein on hemocytes of the wolf spider Pardosa pseudoannulata revealed that CrylAb protein could accumulate in the four-instar and adult spiders via the food chain from transgenic rice expressing CrylAb protein through its prey brown planthoppers with approximate 20-time enrichment, but could not accumulate in hemolymph of the spider. The accumulated CrylAb had no significant effects on several elements of hemolymph including stored energy, calcium ion concentration and apoptosis rate of the hemocytes, indicating that CrylAb could not affect the hemocytes of P. pseudoannulata. [ABSTRACT FROM AUTHOR]

To gain and retain competitive advantages in a competitive business arena, a business cloud-computing platform should continuously strive to offer new services and remain competitive. Unfortunately, it becomes more and more recognized by the industry that a cloud-computing platform could not cover all aspects of IT layers engaged in infrastructure, platform and application. In practice, end users' requests are nearly unlimited; while the services held by a cloud-computing platform is relatively limited, no matter in service category or in service capacity. In view of this challenge, an elastic cloud platform is investigated by recruited outside services that are absent from the cloud platform. Concretely, through dynamically hiring a qualified service on Internet to replace the absent service inside a cloud platform, an elastic cloud platform could nearly provide unlimited capabilities in an outsourcing service way, e.g., computing power, storage, application functions, etc. At last, the validity of the method is evaluated by a case study. [ABSTRACT FROM AUTHOR]

Abstract: With the increasing popularity of cloud computing technologies, more and more service composition processes are enacted and executed in could environment. Compared with the various and approximately infinite application requirements from end users, the web services held by a cloud platform are usually limited. Therefore, it is often a challenging effort to develop a service composition, in such a situation that only part of the functional qualified candidate services could be found inside a cloud platform. In this situation, the absent services will be invocated in a cross-platform way outside the cloud platform. In view of this challenge, a QoS-aware composition method is investigated for supporting cross-platform service invocation in cloud environment. Furthermore, some experiments are deployed to evaluate the method presented in this paper. [Copyright &y& Elsevier]

Abstract: Many scientific workflows are data intensive: large volumes of intermediate datasets are generated during their execution. Some valuable intermediate datasets need to be stored for sharing or reuse. Traditionally, they are selectively stored according to the system storage capacity, determined manually. As doing science on clouds has become popular nowadays, more intermediate datasets in scientific cloud workflows can be stored by different storage strategies based on a pay-as-you-go model. In this paper, we build an intermediate data dependency graph (IDG) from the data provenances in scientific workflows. With the IDG, deleted intermediate datasets can be regenerated, and as such we develop a novel algorithm that can find a minimum cost storage strategy for the intermediate datasets in scientific cloud workflow systems. The strategy achieves the best trade-off of computation cost and storage cost by automatically storing the most appropriate intermediate datasets in the cloud storage. This strategy can be utilised on demand as a minimum cost benchmark for all other intermediate dataset storage strategies in the cloud. We utilise Amazon clouds’ cost model and apply the algorithm to general random as well as specific astrophysics pulsar searching scientific workflows for evaluation. The results show that benchmarking effectively demonstrates the cost effectiveness over other representative storage strategies. [Copyright &y& Elsevier]

Abstract: By sequencing random clones from the venom gland cDNA library of the spider Ornithoctonus huwena, a transcript, named SHL-Ib1, encoding a lectin-like peptide was cloned. The amino acid sequence of the putative mature peptide of SHL-Ib1 is identical, except for seven different residues, with that of SHL-I, a lectin found in the venom of O. huwena. The mature peptides of SHL-Ib1b and SHL-Ib1c are the mutants of SHL-Ib1 with two or three amino acid residues truncated at the C-terminal. The recombinant SHL-Ib1b and SHL-Ib1c were expressed successfully by the yeast expression system and purified by using a combination of ion-exchange and reverse phase high performance liquid chromatography (HPLC). The molecular masses of the two expressed peptides were identified by mass spectrometry, indicating that the C-terminals of the two peptides were not amidated. The two peptides can agglutinate human erythrocytes at minimal concentrations of 0.75 and 1.475mg/ml, respectively. Structure modeling of SHL-Ib1 has given a clue to the low agglutination bioactivities of these recombinant toxins. These lectin-like peptides, due to the small molecular sizes, may have the advantage to investigate the binding mechanism of the lectin and have the potential to be the carrier for drug delivery. [Copyright &y& Elsevier]

In many mammalian species, including pigs, heat stress (HS) detrimentally leads to epithelium damage and increases intestinal permeability. However, the underlying molecular mechanisms are not thoroughly investigated yet. This study aimed to examine the RIP1/RIP3-ERK1/2 signaling pathway that regulates the expression of tight junction proteins in HS-treated pigs. In in vitro cultured intestinal porcine epithelial cells (IPEC-J2), HS induced the expression of tight junction proteins, ZO-1, claudin-1, and claudin-4, that are regulated by the ERK1/2-MAPK signaling pathway. Further, high expression of HSP70 in IPEC-J2 cells induced a significant decrease in receptor-interacting protein 1/3 (RIP1/3), phosphorylated ERK, and tight junction protein claudin-1 (P < 0.05). Necrostatin-1 (A selective inhibitor of RIPK1) suppressed the upregulation of phosphorylated ERK1/2 induced by HS, indicating that the RIP1/RIP3 regulates ERK1/2 phosphorylation in IPEC-J2 under heat stress. In addition, HS significantly damaged the intestinal morphology characterized by reduction of villus length and crypt depth in in vivo porcine model. Moreover, the expression of tight junction, ZO-1, and claudin-4 were downregulated, whereas phosphorylated p38 and ERK1/2 were upregulated in the duodenum of heat-stressed pigs. Interestingly, a decrease in ZO-1 and claudin-1 was observed in the colon, where phosphorylated ERK1/2 was similar to that in the duodenum. Our results demonstrate that RIP1/RIP3-ERK1/2 signaling pathway regulates the expression of tight junction proteins in HS-pigs. This finding further advances the intestinal barrier function's underlying mechanisms associated with signaling regulation. • A heat stress induced porcine inflammatory bowel disease model was constructed successfully. • Heat stress induced down – regulation of tight junction proteins play a vital role in the development inflammatory bowel disease in pigs. • Heat stress induced down-regulation of tight junction proteins was via ERK1/2 signaling pathway. [ABSTRACT FROM AUTHOR]

• Recommend the more and novel items based on accurate and diverse recommendations. • Mixing multiple recommendation technologies to improve recommendation performance. • The system is based on rating, which makes the recommendation more objective. • Clustering strategies are used to reduce recommended consumption. Recommendation system (RS) is a technology that provides accurate recommendations to users. However, it is not comprehensive to only consider the accuracy of the recommendation because users have different requirements. To improve the comprehensive performance, this paper presents a hybrid recommendation model based on many-objective optimization, which can simultaneously optimize the accuracy, diversity, novelty and coverage of recommendation. This model enhances the robustness of recommendations by mixing three different basic recommendation technologies. Additionally, we solve it with many-objective evolutionary algorithm (MaOEA) and test it extensively. Experimental results demonstrate the effectiveness of the presented model, which can provide the recommendations with more and novel items on the basis of accurate and diverse. [ABSTRACT FROM AUTHOR]

Di-(2-ethylhexyl) phthalate (DEHP) is the most widely used plasticizer and a representative endocrine disrupting chemical. The toxicological effects of DEHP on environmental and human health have been widely investigated. In this study, the DEHP-degrading bacterial strain RL-JC02 was isolated from red soil with long-term usage of plastic mulch, and it was identified as Gordonia terrae by 16S rRNA gene analysis coupled with physiological and biochemical characterization. The biodegrading capacity of different phthalic acid esters and related intermediates was investigated as well as the performance of strain RL-JC02 under different environmental conditions, such as temperature, pH, salinity and DEHP concentration. Specifically, strain RL-JC02 showed good tolerance to low pH, with 86.6% of DEHP degraded under the initial pH of 5.0 within 72 h. The metabolic pathway of DEHP was examined by metabolic intermediate identification via a high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) analysis in which DEHP was hydrolyzed into phthalic acid (PA) and 2-ethylhexanol (2-EH) via mono (2-ethylhexyl) phthalate (MEHP). PA and 2-EH were further utilized through the protocatechuic acid metabolic pathway and β-oxidation via protocatechuic acid and 2-ethylhexanoic acid, respectively. The application potential of strain RL-JC02 was confirmed through the bioremediation of artificial DEHP-contaminated red soil showing 91.8% DEHP degradation by strain RL-JC02 within 30 d. The kinetics analysis of DEHP degradation by strain RL-JC02 in soil demonstrated that the process followed the modified Gompertz model. Meanwhile, the cell concentration monitoring of strain RL-JC02 in soil with absolute quantification polymerase chain reaction (qPCR) suggested that strain RL-JC02 survived well during bioremediation. This study provides sufficient evidence of a robust degrader for the bioremediation of PAE-contaminated red soil. Unlabelled Image • One DEHP degrading bacterial strain RL-JC02 was isolated from red soil. • DEHP was degraded via the typical de-esterification pathway. • Bioremediation could accelerate the elimination of DEHP in red soil. • The kinetics of bioremediation fitted with the modified Gompertz model. • Strain RL-JC02 survived well during bioremediation. [ABSTRACT FROM AUTHOR]

In recent years, global climate change and pollution of the marine environment have caused large-scale coral deaths and severe damages to coral reef ecosystems. Numerous studies have shown that coral diseases are closely related to microorganisms. And microplastics (MPs) are a potential threat to corals. In marine ecosystems, MPs are an emerging contaminant. MPs have a strong adsorption effect on pollutants in the water environment, and they are very easily colonized by microorganisms to form biofilms. Biofilms may accumulate many pathogens, increasing the probability of coral disease. However, there is no report about the composition of biofilms on the surface of microplastics in coral growth areas. In this study, nine kinds of MPs were chosen in the experiments, which are commonly found in the ocean. Four stakeout points were selected in the coral area. Biofilms were cultivated in natural environment. The composition and distribution of biofilms on the surface of the MPs were analyzed by 16 S rRNA sequencing. The characteristics of biofilms were observed by scanning electron microscopy (SEM). The experimental results show that the species composition and abundance distribution of the biofilm on the MP surface are significantly different from the surrounding seawater. The type of MPs and the stake out point are important factors affecting the structure of the biofilm bacterial community. Compared to seawater samples, MPs are enriched with certain dominant bacteria such as Vibrionaceae , Rhodobacteraceae , Flavobacteraceae , Microtrichaceae and Sphingomonadaceae. Among them, Vibrionaceae , Rhodobacteraceae and Flavobacteraceae are closely related to the tissue damage of stony corals, and Vibrios are also the main pathogens of coral albinism. In addition, Pseudomonas and Bbellvibrio cholerae are also detected on the MPs biofilm. SEM graphs of the MPs after culture could clearly observe rod-shaped bacteria and Streptococci. This study can provide a new direction for the study of coral toxicology by MPs and provide basic data for the toxicology research of MPs. • It is the first to study the structure of microplastic surface biofilms in coral areas. • This study used natural culture methods to cultivate biofilms. • The structure of the biofilms obviously different from the seawater. • The biofilms are closely related to the environment and the type of microplastics. • Vibrio and Rhodobacter are the predominant bacteria of biofilms. [ABSTRACT FROM AUTHOR]

The detection of microplastics and nanoplastics in the environment, especially plastic particles in aquatic environments in situ, still faces challenges due to the limitations of current methods, instruments and size of plastic particles. This paper evaluates the potential of surface-enhanced Raman spectroscopy for the analysis of microplastics and nanoplastics. The condition of different tests including the volume ratio of sample to silver colloid, the concentrations of NaCl, and the concentrations of the samples, are assessed for the study of microplastics and nanoplastics (polystyrene (PS), polyethylene (PE) and polypropylene (PP)) in pure water and seawater. A method based on SERS, that uses silver colloid as the active substrate, is developed for the qualitative analysis of microplastics and nanoplastics in aquatic environments. The particle sizes of microplastics and nanoplastics include 100 nm, 500 nm and 10 μm. The Raman signals of microplastics and nanoplastics in pure water and seawater both show good enhancement efficiency. The optimal enhancement factor is 4 × 104. The SERS-based detection method overcomes the limitations of microplastics and nanoplastics in liquids and can detect 100 nm plastics down to 40 μg/mL. It provides more possibility for the rapid detection of microplastics and nanoplastics in aquatic environments in the future. Unlabelled Image • A method for detecting micro/nanoplastics in water environment was developed. • Plastic particles in the size range from nanometers to microns can be detected. • Effective identification of different types of plastic particles. • Capable of detecting 100 nm plastic particles down to 40 μg/mL. [ABSTRACT FROM AUTHOR]

Background: Little is known about cause and intervention for alanine aminotransferase (ALT) elevation after complete viral suppression in patients with chronic hepatitis B (CHB).Methods: In this prospective cohort study, patients with CHB who were treated with nucleos(t)ide analogs and maintained undetectable levels of hepatitis B virus (HBV) deoxyribonucleic acid (DNA) for at least 6 months were enrolled. Patients were followed up at 6-month intervals, and anthropometric, biochemical, and virological assessments were performed.Results: Of 1965 patients with median follow-up of 18.36 months, one third of patients experienced ALT elevation. Baseline high body mass index ([BMI] defined as ≥25 kg/m2), younger age, and liver cirrhosis independently increased the risk of longitudinal ALT elevation. At the end of follow-up, 89 (4.8%) patients reverted to low BMI, and 92 (5.0%) developed to high BMI. Compared with persistent high BMI, reversion to low BMI reduced the risk of ALT elevation (adjusted odds ratio [aOR], 0.38; 95% confidence interval [CI], 0.19-0.77); compared with persistent low BMI, onset of high BMI increased the risk of ALT elevation (aOR, 1.78; 95% CI, 1.02-3.11).Conclusions: High BMI is an independent predictor for ALT elevation after complete HBV DNA suppression. Improvement of BMI may have a beneficial effect on ALT normalization and even long-term outcomes. [ABSTRACT FROM AUTHOR]

Locating node technology, as the most fundamental component of wireless sensor networks (WSNs) and internet of things (IoT), is a pivotal problem. Distance vector-hop technique (DV-Hop) is frequently used for location node estimation in WSN, but it has a poor estimation precision. In this paper, a multi-objective DV-Hop localization algorithm based on NSGA-II is designed, called NSGA-II-DV-Hop. In NSGA-II-DV-Hop, a new multi-objective model is constructed, and an enhanced constraint strategy is adopted based on all beacon nodes to enhance the DV-Hop positioning estimation precision, and test four new complex network topologies. Simulation results demonstrate that the precision performance of NSGA-II-DV-Hop significantly outperforms than other algorithms, such as CS-DV-Hop, OCS-LC-DV-Hop, and MODE-DV-Hop algorithms. [ABSTRACT FROM AUTHOR]

A bat algorithm (BA) is a heuristic algorithm that operates by imitating the echolocation behavior of bats to perform global optimization. The BA is widely used in various optimization problems because of its excellent performance. In the bat algorithm, the global search capability is determined by the parameter loudness and frequency. However, experiments show that each operator in the algorithm can only improve the performance of the algorithm at a certain time. In this paper, a novel bat algorithm with multiple strategies coupling (mixBA) is proposed to solve this problem. To prove the effectiveness of the algorithm, we compared it with CEC2013 benchmarks test suits. Furthermore, the Wilcoxon and Friedman tests were conducted to distinguish the differences between it and other algorithms. The results prove that the proposed algorithm is significantly superior to others on the majority of benchmark functions. [ABSTRACT FROM AUTHOR]

Due to the dynamic nature of the underlying high-performance infrastructures for scientific workflows such as grid and cloud computing, failures of timely completion of important scientific activities, namely, temporal violations, often take place. Unlike conventional exception handling on functional failures, nonfunctional QoS failures such as temporal violations cannot be passively recovered. They need to be proactively prevented through dynamically monitoring and adjusting the temporal consistency states of scientific workflows at runtime. However, current research on workflow temporal verification mainly focuses on runtime monitoring, while the adjusting strategy for temporal consistency states, namely, temporal adjustment, has so far not been thoroughly investigated. For this issue, two fundamental problems of temporal adjustment, namely, where and how, are systematically analyzed and addressed in this paper. Specifically, a novel minimum probability time redundancy-based necessary and sufficient adjustment point selection strategy is proposed to address the problem of where and an innovative genetic-algorithm-based effective and efficient local rescheduling strategy is proposed to tackle the problem of how. The results of large-scale simulation experiments with generic workflows and specific real-world applications demonstrate that our temporal adjustment strategy can remarkably prevent the violations of both local and global temporal constraints in scientific workflows. [ABSTRACT FROM AUTHOR]