Kinetic framework for ligation by an efficient RNA ligase ribozyme

The class I RNA ligase ribozyme, isolated previously from random sequences, performs an efficient RNA ligation reaction. It ligates two substrate RNAs, promoting the attack of the 3'-hydroxyl of one substrate upon the 5'-triphosphate of the other substrate with release of pyrophosphate. This ligation reaction has similarities to the reaction catalyzed by RNA polymerases. Using data from steady-state kinetic measurements and pulse-chase/pH-jump experiments, we have constructed minimal kinetic frameworks for two versions of the class I ligase, named 207t and 210t. For both ligases, as well as for the self-ligating parent ribozyme, the rate constant for the chemical step (k(c)) is log-linear with pH in the range 5.7-8.0. At physiological pH, the k(c) is 100 min(-1), a value similar to those reported for the fastest naturally occurring ribozymes. At higher pH, product release is limiting for both 207t and 210t. The 210t ribozyme, with its faster product release, attains multiple-turnover rates (k(cat) = 360 min(-1), pH 9.0) exceeding those of 207t and other reported ribozyme reactions. The kinetic framework for the 210t ribozyme describes the limits of this catalysis and suggests how key steps can be targeted for improvement using design or combinatorial approaches.     

Swarm: A federated cloud framework for large-scale variant analysis

Genomic data analysis across multiple cloud platforms is an ongoing challenge, especially when large amounts of data are involved. Here, we present Swarm, a framework for federated computation that promotes minimal data motion and facilitates crosstalk between genomic datasets stored on various cloud platforms. We demonstrate its utility via common inquiries of genomic variants across BigQuery in the Google Cloud Platform (GCP), Athena in the Amazon Web Services (AWS), Apache Presto and MySQL. Compared to single-cloud platforms, the Swarm framework significantly reduced computational costs, run-time delays and risks of security breach and privacy violation.     

CryptoGA: a cryptosystem based on genetic algorithm for cloud data security

Cluster Computing - Cloud Computing is referred to as a set of hardware and software that are being combined to deliver various services of computing. The cloud keeps the services for delivery of...     

The TIM-barrel fold: a versatile framework for efficient enzymes

Recent studies on triosephosphate isomerase (TIM)-barrel enzymes highlight the remarkable versatility of the TIM-barrel scaffold. At least 15 distinct enzyme families use this framework to generate the appropriate active site geometry, always at the C-terminal end of the eight parallel beta-strands of the barrel. Sequence and structure comparisons now suggest that many of the TIM-barrel enzymes are evolutionarily related. Common structural properties of TIM-barrel enzymes are discussed.     

BioJava: an open-source framework for bioinformatics

SUMMARY: BioJava is a mature open-source project that provides a framework for processing of biological data. BioJava contains powerful analysis and statistical routines, tools for parsing common file formats and packages for manipulating sequences and 3D structures. It enables rapid bioinformatics application development in the Java programming language. AVAILABILITY: BioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.5 or higher. All queries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists.     

AutoMigrate: a framework for developing intelligent,self-managing cloud services with maximum availability

Cloud services are on-demand services provided to end-users over the Internet and hosted by cloud service providers. A cloud service consists of a set of interacting applications/processes running on one or more interconnected VMs. Organizations are increasingly using cloud services as a cost-effective means for outsourcing their IT departments. However, cloud service availability is not guaranteed by cloud service providers, especially in the event of anomalous circumstances that spontaneously disrupt availability including natural disasters, power failure, and cybersecurity attacks. In this paper, we propose a framework for developing intelligent systems that can monitor and migrate cloud services to maximize their availability in case of cloud disruption. The framework connects an autonomic computing agent to the cloud to automatically migrate cloud services based on anticipated cloud disruption. The autonomic agent employs a modular design to facilitate the incorporation of different techniques for deciding when to migrate cloud services, what cloud services to migrate, and where to migrate the selected cloud services. We incorporated a virtual machine selection algorithm for deciding what cloud services to migrate that maximizes the availability of high priority services during migration under time and network bandwidth constraints. We implemented the framework and conducted experiments to evaluate the performance of the underlying techniques. Based on the experiments, the use of this framework results in less down-time due to migration, thereby leading to reduced cloud service disruption.     

A strengthening plan for enterprise information security based on cloud computing

Cloud computing environment came about in order to effectively manage and use enormous amount of data that have become available with the development of the Internet. Cloud computing service is widely used not only to manage the users’ IT resources, but also to use enterprise IT resources in an effective manner. Various security threats have occurred while using cloud computing and plans for reaction are much needed, since they will eventually elevate to security threats to enterprise information. Plans to strengthen the security of enterprise information by using cloud security will be proposed in this research. These cloud computing security measures must be supported by the governmental policies. Publications on guidelines to information protection will raise awareness among the users and service providers. System of reaction must be created in order to constantly monitor and to promptly respond to any security accident. Therefore, both technical countermeasures and governmental policy must be supported at the same time. Cloud computing service is expanding more than ever, thus active research on cloud computing security is expected.     

A framework for SLA management in cloud computing for informed decision making

In cloud computing, service providers offer cost-effective and on-demand IT services to service users on the basis of Service Level Agreements (SLAs). However the effective management of SLAs in cloud computing is essential for the service users to ensure that they achieve the desired outcomes from the formed service. In this paper, we introduce a SLA management framework that will enable service users to select the best available service provider on the basis of its reputation and then monitor the run time performance of the service provider to determine whether or not it will fulfill its promise defined in the SLA. Such analysis will assist the service user to make an informed decision about the continuation of service with the service provider.     

Towards a framework for monitoring cloud application platforms as sensor networks

With the continued growth in software environments on cloud application platforms, self-management at the Platform-as-a-Service (PaaS) level has become a pressing concern, and the run-time monitoring, analysis and detection of critical situations are all fundamental requirements if we are to achieve autonomic behaviour in complex PaaS environments. In this paper we focus on cloud application platforms offering their customers a range of generic built-in re-usable services. By identifying key characteristics of these complex dynamic systems, we compare cloud application platforms to distributed sensor networks, and investigate the viability of exploiting these similarities with a case study. We treat cloud data storage services as “virtual” sensors constantly emitting monitoring data, such as numbers of connections and storage space availability, which are then analysed by the central component of a monitoring framework so as to detect and react to SLA violations. We discuss the potential benefits, as well as some shortcomings, of adopting this approach.     

北京市生态安全格局及城市增长预景

在快速城市化和城市生态安全面临巨大挑战的时代背景下,构建生态安全格局是实现区域和城市生态安全的基本保障和重要途径.在梳理国内外生态安全格局研究进展的基础上,提出基于景观安全格局理论的北京市生态安全格局网络和城市发展空间格局.通过对北京市水文、地质灾害、生物多样性保护、文化遗产和游憩过程的系统分析,运用GIS和空间分析技术,判别出维护上述各种过程安全的     

基于生态-产业共生关系的林业生态安全测度方法构想

通过对林业生态安全内涵构成的研究和对现有测度方法的比较分析,发现国内外林业生态安全测度研究中存在“就生态论生态”的预警滞后性、评价指标体系及权重设定的主观性、指标体系和特征指数难以优势互补、生态安全性判据缺乏客观依据等问题.为解决这些问题,需要基于生态与产业系统的共生关系研究林业生态安全测度的新方法.首先,研究林业生态安全的压力-状态-影响-响应结构模型和结构方程模型(SEM)的构建方法,从而为评价指标体系的构建和权重的确定提供了理论依据和结构化、定量化方法.然后,通过寻求指标体系和特征指数的有机结合,得出描述林业生态安全演变趋势的性质和程度的特征指数——生态-产业共生度和成熟度.由此提出确定林业生态安全阈值和底线的定量化方法,并建立林业生态安全双特征判断矩阵,从而将林业生态安全度分为3个安全区间、6个安全等级和4个预警级别.最后,综合以上成果,构建了基于生态-产业共生关系的林业生态安全测度方法的整体框架:目标-手段树和技术路线.根据新方法的构建机理,所得出的林业生态安全测度和预警信息具有主观性弱、预测性强、特征指数值的生态经济意义明确、便于追溯问题的原因等技术优势,有利于林业生态安全的监控和管理.     

Yucca: an efficient algorithm for small-molecule docking

In this paper, we present a new algorithm, which is based on an efficient heuristic for local search, for rigid protein-small-molecule docking. We tested our algorithm, called Yucca, on the recent 100-complex benchmark, using the conformer generator OMEGA to generate a set of low-energy conformers. The results showed that Yucca is competitive both in terms of algorithm efficiency and docking accuracy.     

SHARE-ABE: an efficient and secure data sharing framework based on ciphertext-policy attribute-based encryption and Fog computing

Attribute-based encryption (ABE) is an access control mechanism that ensures efficient data sharing among dynamic groups of users by setting up access structures indicating who can access what. However, ABE suffers from expensive computation and privacy issues in resource-constrained environments such as IoT devices. In this paper, we present SHARE-ABE, a novel collaborative approach for preserving privacy that is built on top of Ciphertext-Policy Attribute-Based Encryption (CP-ABE). Our approach uses Fog computing to outsource the most laborious decryption operations to Fog nodes. The latter collaborate to partially decrypt the data using an original and efficient chained architecture. Additionally, our approach preserves the privacy of the access policy by introducing false attributes. Furthermore, we introduce a new construction of a collaboration attribute that allows users within the same group to combine their attributes while satisfying the access policy. Experiments and analyses of the security properties demonstrate that the proposed scheme is secure and efficient especially for resource-constrained IoT devices.

     

Invasion triangle: an organizational framework for species invasion

Species invasion is a complex, multifactor process. To encapsulate this complexity into an intuitively appealing, simple, and straightforward manner, we present an organizational framework in the form of an invasion triangle. The invasion triangle is an adaptation of the disease triangle used by plant pathologists to help envision and evaluate interactions among a host, a pathogen, and an environment. Our modification of this framework for invasive species incorporates the major processes that result in invasion as the three sides of the triangle: (1) attributes of the potential invader; (2) biotic characteristics of a potentially invaded site; and (3) environmental conditions of the site. The invasion triangle also includes the impact of external influences on each side of the triangle, such as climate and land use change. This paper introduces the invasion triangle, discusses how accepted invasion hypotheses are integrated in this framework, describes how the invasion triangle can be used to focus research and management, and provides examples of application. The framework provided by the invasion triangle is easy to use by both researchers and managers and also applicable at any level of data intensity, from expert opinion to highly controlled experiments. The organizational framework provided by the invasion triangle is beneficial for understanding and predicting why species are invasive in specific environments, for identifying knowledge gaps, for facilitating communication, and for directing management in regard to invasive species.     

An explainable and efficient deep learning framework for video anomaly detection

Cluster Computing - Deep learning-based video anomaly detection methods have drawn significant attention in the past few years due to their superior performance. However, almost all the leading...     

CECT: computationally efficient congestion-avoidance and traffic engineering in software-defined cloud data centers

The proliferation of cloud data center applications and network function virtualization (NFV) boosts dynamic and QoS dependent traffic into the data centers network. Currently, lots of network routing protocols are requirement agnostic, while other QoS-aware protocols are computationally complex and inefficient for small flows. In this paper, a computationally efficient congestion avoidance scheme, called CECT, for software-defined cloud data centers is proposed. The proposed algorithm, CECT, not only minimizes network congestion but also reallocates the resources based on the flow requirements. To this end, we use a routing architecture to reconfigure the network resources triggered by two events: (1) the elapsing of a predefined time interval, or, (2) the occurrence of congestion. Moreover, a forwarding table entries compression technique is used to reduce the computational complexity of CECT. In this way, we mathematically formulate an optimization problem and define a genetic algorithm to solve the proposed optimization problem. We test the proposed algorithm on real-world network traffic. Our results show that CECT is computationally fast and the solution is feasible in all cases. In order to evaluate our algorithm in term of throughput, CECT is compared with ECMP (where the shortest path algorithm is used as the cost function). Simulation results confirm that the throughput obtained by running CECT is improved up to 3× compared to ECMP while packet loss is decreased up to 2×.     

Taking the long view: an emerging framework for translational psychiatric science

Understood in their historical context, current debates about psychiatric classification, prompted by the publication of the DSM‐5, open up new opportunities for improved translational research in psychiatry. In this paper, we draw lessons for translational research from three time slices of 20th century psychiatry. From the first time slice, 1913 and the publication of Jaspers' General Psychopathology, the lesson is that translational research in psychiatry requires a pluralistic approach encompassing equally the sciences of mind (including the social sciences) and of brain. From the second time slice, 1959 and a conference in New York from which our present symptom‐based classifications are derived, the lesson is that, while reliability remains the basis of psychiatry as an observational science, validity too is essential to effective translation. From the third time slice, 1997 and a conference on psychiatric classification in Dallas that brought together patients and carers with researchers and clinicians, the lesson is that we need to build further on collaborative models of research combining expertise‐by‐training with expertise‐by‐experience. This is important if we are to meet the specific challenges to translation presented by the complexity of the concept of mental disorder, particularly as reflected in the diversity of desired treatment outcomes. Taken together, these three lessons – a pluralistic approach, reliability and validity, and closer collaboration among relevant stakeholders – provide an emerging framework for more effective translation of research into practice in 21st century psychiatry.