Definition and Categorization of Dew Computing

Dew computing is an emerging new research area and has great potentials in applications. In this paper, we propose a revised definition of dew computing. The new definition is: Dew computing is an on-premises computer software-hardware organization paradigm in the cloud computing environment where the on-premises computer provides functionality that is independent of cloud services and is also collaborative with cloud services. The goal of dew computing is to fully realize the potentials of on-premises computers and cloud services. This definition emphasizes two key features of dew computing: independence and collaboration. Furthermore, we propose a group of dew computing categories. These categories may inspire new applications

Linkage analysis of systolic blood pressure: a score statistic and computer implementation

A genome-wide linkage analysis was conducted on systolic blood pressure using a score statistic. The randomly selected Replicate 34 of the simulated data was used. The score statistic was applied to the sibships derived from the general pedigrees. An add-on R program to GENEHUNTER was developed for this analysis and is freely available

Group analysis and conservation laws of an integrable Kadomtsev–Petviashvili equation

In this paper, an integrable KP equation is studied using symmetry and conservation laws. First, on the basis of various cases of coefficients, we construct the infinitesimal generators. For the special case, we get the corresponding geometry vector fields, and then from known soliton solutions we derive new soliton solutions. In addition, the explicit power series solutions are derived. Lastly, nonlinear self-adjointness and conservation laws are constructed with symmetries

Get Out of the Valley: Power-Efficient Address Mapping for GPUs

GPU memory systems adopt a multi-dimensional hardware structure to provide the bandwidth necessary to support 100s to 1000s of concurrent threads. On the software side, GPU-compute workloads also use multi-dimensional structures to organize the threads. We observe that these structures can combine unfavorably and create significant resource imbalance in the memory subsystem causing low performance and poor power-efficiency. The key issue is that it is highly application-dependent which memory address bits exhibit high variability. To solve this problem, we first provide an entropy analysis approach tailored for the highly concurrent memory request behavior in GPU-compute workloads. Our window-based entropy metric captures the information content of each address bit of the memory requests that are likely to co-exist in the memory system at runtime. Using this metric, we find that GPU-compute workloads exhibit entropy valleys distributed throughout the lower order address bits. This indicates that efficient GPU-address mapping schemes need to harvest entropy from broad address-bit ranges and concentrate the entropy into the bits used for channel and bank selection in the memory subsystem. This insight leads us to propose the Page Address Entropy (PAE) mapping scheme which concentrates the entropy of the row, channel and bank bits of the input address into the bank and channel bits of the output address. PAE maps straightforwardly to hardware and can be implemented with a tree of XOR-gates. PAE improves performance by 1.31 x and power-efficiency by 1.25 x compared to state-of-the-art permutation-based address mapping

An Agent Approach to Spatial Information Grid Architecture Design

Spatial information grid (SIG) is a spatial information infrastructure that has the capability of providing services on-demand. SIG is a distributed network environment, which links spatial data resources, computing resources, storage resources, software, tools and users. SIG can integrate massive distributed heterogeneous spatial information resources, provides uniform management and process, and, furthermore, coordinate different resources to complete large-scale and complex spatial tasks and applications. In this paper, agent technology is adopted to construct a SIG framework, which contains three layers: users/applications layer, agent services layer and information layer. Different applications can get their spatial information via agent services, and agent services make the procedure of navigating and accessing spatial information transparent to users. Also, the implementation issues of the framework are discussed in detail, including Geo-Agents, an agent-based distributed GIS system, spatial information management, collaboration and parallel mechanism, load control strategy, and a sample

Interleukin-6 gene -572G/C polymorphism and prostate cancer risk

Background: The aim of the present study was to determine whether the interleukin-6 (IL-6) -572G/C polymorphism correlates with prostate cancer.Methods: According to inclusion and exclusion criteria, the association of the IL-6 -572G/C polymorphism with prostate cancer was searched in databases and analyzed using comprehensive meta-analysis software. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of the associations.Results: We considered a total of six case-control studies including 2237 patients and 1754 controls and the meta-analysis results showed significant association between the IL-6 -572G/C polymorphism and prostate cancer risk(CC vs GG: OR = 0.49, 95% CI =0.37-0.65;CG vs GG: OR =0.71, 95% CI = 0.58-0.87; the dominant model: OR =0.65, 95% CI = 0.54-0.79;the recessive model: OR =0.70, 95% CI = 0.58-0.85). In stratified analyses by ethnicity, significant associations were found among Asian populations. However, no significant association was found in Caucasian populations.Conclusion: Our findings demonstrated that the -572G/C polymorphism of the IL-6 gene may be a risk factor for the development of prostate cancer in Asians.Keywords: Prostate cancer, IL-6 polymorphisms, risk

A Hierarchical Component-based WebGIS and Its Key Technologies

A practical hierarchical component-based WebGIS model referred to as Geo-Union is presented. Geo-Union consists of four layers: storage layer, service layer, component layer and application layer. Service layer is partitioned into another two layers: Geo-Union client and Geo-Union server. The architectures and object diagram of each layer in Geo-Union are discussed in details. After that, four key technologies adopted in Geo-Union (spatial data model, ORDB, spatial index and spatial cache) are summarized and analyzed, especially the spatial cache framework of Geo-Union. At last, some future works in WebGIS, such as interoperability, security, distributed computing and intelligent computing, are indicated and simply explored

Programming the Nucleation of DNA Brick Self-Assembly with a Seeding Strand.

Recently, the DNA brick strategy has provided a highly modular and scalable approach for the construction of complex structures, which can be used as nanoscale pegboards for the precise organization of molecules and nanoparticles for many applications. Despite the dramatic increase of structural complexity provided by the DNA brick method, the assembly pathways are still poorly understood. Herein, we introduce a "seed" strand to control the crucial nucleation and assembly pathway in DNA brick assembly. Through experimental studies and computer simulations, we successfully demonstrate that the regulation of the assembly pathways through seeded growth can accelerate the assembly kinetics and increase the optimal temperature by circa 4-7 °C for isothermal assembly. By improving our understanding of the assembly pathways, we provide new guidelines for the design of programmable pathways to improve the self-assembly of DNA nanostructures.Natural Science Foundation of China (grants 51672022, 51302010) NSF (grants DMR-1654485 and ECCS-1807568) Semiconductor Research Corporation (grant 2836.002) EPSRC Tier-2 (capital grant EP/P020259/1