Religion and spirituality: Linkages to physical health.

Evidence is presented that bears on 9 hypotheses about the link between religion or spirituality and mortality, morbidity, disability, or recovery from illness. In healthy participants, there is a strong, consistent, prospective, and often graded reduction in risk of mortality in church/service attenders. This reduction is approximately 25% after adjustment for confounders. Religion or spirituality protects against cardiovascular disease, largely mediated by the healthy lifestyle it encourages. Evidence fails to support a link between depth of religiousness and physical health. In patients, there are consistent failures to support the hypotheses that religion or spirituality slows the progression of cancer or improves recovery from acute illness but some evidence that religion or spirituality impedes recovery from acute illness. The authors conclude that church/service attendance protects healthy people against death. More methodologically sound studies are needed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A comparative study of two approaches for supporting optimal network location queries

Given a set S of sites and a set O of weighted objects, an optimal location query finds the location(s) where introducing a new site maximizes the total weight of the objects that are closer to the new site than to any other site. With such a query, for instance, a franchise corporation (e.g., McDonald’s) can find a location to open a new store such that the number of potential store customers (i.e., people living close to the store) is maximized. Optimal location queries are computationally complex to compute and require efficient solutions that scale with large datasets. Previously, two specific approaches have been proposed for efficient computation of optimal location queries. However, they both assume p-norm distance (namely, L₁ and L₂/Euclidean); hence, they are not applicable where sites and objects are located on spatial networks. In this article, we focus on optimal network location (ONL) queries, i.e., optimal location queries in which objects and sites reside on a spatial network. We introduce two complementary approaches, namely EONL (short for Expansion-based ONL) and BONL (short for Bound-based ONL), which enable efficient computation of ONL queries with datasets of uniform and skewed distributions, respectively. Moreover, with an extensive experimental study we verify and compare the efficiency of our proposed approaches with real world datasets, and we demonstrate the importance of considering network distance (rather than p-norm distance) with ONL queries.     

Efficient indexing and retrieval of large-scale geo-tagged video databases

We are witnessing a significant growth in the number of smartphone users and advances in phone hardware and sensor technology. In conjunction with the popularity of video applications such as YouTube, an unprecedented number of user-generated videos (UGVs) are being generated and consumed by the public, which leads to a Big Data challenge in social media. In a very large video repository, it is difficult to index and search videos in their unstructured form. However, due to recent development, videos can be geo-tagged (e.g., locations from GPS receiver and viewing directions from digital compass) at the acquisition time, which can provide potential for efficient management of video data. Ideally, each video frame can be tagged by the spatial extent of its coverage area, termed Field-Of-View (FOV). This effectively converts a challenging video management problem into a spatial database problem. This paper attacks the challenges of large-scale video data management using spatial indexing and querying of FOVs, especially maximally harnessing the geographical properties of FOVs. Since FOVs are shaped similar to slices of pie and contain both location and orientation information, conventional spatial indexes, such as R-tree, cannot index them efficiently. The distribution of UGVs’ locations is non-uniform (e.g., more FOVs in popular locations). Consequently, even multilevel grid-based indexes, which can handle both location and orientation, have limitations in managing the skewed distribution. Additionally, since UGVs are usually captured in a casual way with diverse setups and movements, no a priori assumption can be made to condense them in an index structure. To overcome the challenges, we propose a class of new R-tree-based index structures that effectively harness FOVs’ camera locations, orientations and view-distances, in tandem, for both filtering and optimization. We also present novel search strategies and algorithms for efficient range and directional queries on our indexes. Our experiments using both real-world and large synthetic video datasets (over 30 years’ worth of videos) demonstrate the scalability and efficiency of our proposed indexes and search algorithms.     

Effect of polyaluminium chloride on phosphorus removal in constructed wetlands treated with swine wastewater

Total phosphorus (TP) removal in aged constructed wetlands poses a challenge, especially when treated with swine wastewater with high concentrations of phosphorus (P). Our earlier studies with anaerobic lagoon swine wastewater treatment in constructed wetlands showed a decline in P removal (45-22%) with increased years of operation. These particular wetlands have been treated with swine wastewater every year since the first application in 1997. Preliminary lab-scale studies were conducted to evaluate the efficiency of polyaluminium chloride (PAC) in the removal of phosphate-P (PO4-P) from swine wastewater. The experimental objective was to increase the phosphorus treatment efficiency in constructed wetland by adding PAC as a precipitating agent. PAC was added by continuous injection to each wetland system at a rate of 3 L day(-1) (1:5 dilution of concentrated PAC). Swine wastewater was added from an anaerobic lagoon to four constructed wetland cells (11m wide x 40m long) at TP loads of 5.4-6.1 kg ha(-1) day(-1) in two experimental periods, September to November of 2008 and 2009. Treatment efficiency of two wetland systems: marsh-pond-marsh (M-P-M) and continuous marsh (CM) was compared. The wetlands were planted with cattails (Typha latifolia L.) and bulrushes (Scirpus americanus). In 2008, PAC treatment showed an increase of 27.5 and 40.8% of TP removal over control in M-P-M and CM respectively. Similar trend was also observed in the following year. PAC as a flocculant and precipitating agent showed potential to enhance TP removal in constructed wetlands treated with swine wastewater.     

ProDA: An End-to-End Wavelet-Based OLAP System for Massive Datasets

ProDA employs wavelets to support exact, approximate, and progressive OLAP queries on large multidimensional datasets, while keeping update costs relatively low. ProDA not only supports online execution of ad hoc analytical queries on massive datasets, but also extends the set of supported analytical queries to include the entire family of polynomial aggregate queries as well as the new class of plot queries.     

A hybrid aggregation and compression technique for road network databases

Vector data and in particular road networks are being queried, hosted and processed in many application domains such as in mobile computing. Many client systems such as PDAs would prefer to receive the query results in unrasterized format without introducing an overhead on overall system performance and result size. While several general vector data compression schemes have been studied by different communities, we propose a novel approach in vector data compression which is easily integrated within a geospatial query processing system. It uses line aggregation to reduce the number of relevant tuples and Huffman compression to achieve a multi-resolution compressed representation of a road network database. Our experiments performed on an end-to-end prototype verify that our approach exhibits fast query processing on both client and server sides as well as high compression ratio.

Processing Optimal Sequenced Route Queries Using Voronoi Diagrams

The Optimal Sequenced Route (OSR) query strives to find a route of minimum length starting from a given source location and passing through a number of typed locations in a specific sequence imposed on the types of the locations. In this paper, we propose a pre-computation approach to OSR query in both vector and metric spaces. We exploit the geometric properties of the solution space and theoretically prove its relation to additively weighted Voronoi diagrams. Our approach recursively accesses these diagrams to incrementally build the OSR. Introducing the analogous diagrams for the space of road networks, we show that our approach is also efficiently applicable to this metric space. Our experimental results verify that our pre-computation approach outperforms the previous index-based approaches in terms of query response time. This research has been funded in part by NSF grants EEC-9529152 (IMSC ERC), IIS-0238560 (PECASE), IIS-0324955 (ITR), IIS-0534761, and unrestricted cash gifts from Google and Microsoft. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

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Super-Streaming: A New Object Delivery Paradigm for Continuous Media Servers

A number of studies have focused on the design of continuous media, CM, (e.g., video and audio) servers to support the real-time delivery of CM objects. These systems have been deployed in local environments such as hotels, hospitals and cruise ships to support media-on-demand applications. They typically stream CM objects to the clients with the objective of minimizing the buffer space required at the client site. This objective can now be relaxed due to the availability of inexpensive storage devices at the client side. Therefore, we propose a Super-streaming paradigm that can utilize the client side resources in order to improve the utilization of the CM server. To support super-streaming, we propose a technique to enable the CM servers to deliver CM objects at a rate higher than their display bandwidth requirement. We also propose alternative admission control policies to downgrade super-streams in favor of regular streams when the resources are scarce. We demonstrate the superiority of our paradigm over streaming with both analytical and simulation models.Moreover, new distributed applications such as distant-learning, digital libraries, and home entertainment require the delivery of CM objects to geographically disbursed clients. For quality purposes, recently many studies proposed dedicated distributed architectures to support these types of applications. We extend our super-streaming paradigm to be applicable in such distributed architectures. We propose a sophisticated resource management policy to support super-streaming in the presence of multiple servers, network links and clients. Due to the complexity involved in modeling these architectures, we only evaluate the performance of super-streaming by a simulation study.     

Coating Effects on Transient Cooling a Hot Spherical Body

A numerical solution is carried out to treat the transient cooling problem with conduction and radiation for a hot spherical body covered with a cold coating material. The solution includes the equations of radiative transfer, coupled with a transient energy equation that contains both radiative and conductive terms. The radiative transfer equation was solved by the discrete ordinates method, and a parmetric study was performed by changing various physical parameters such as the optical thicknesses, thermal conductivity of the coating, emissivity, and diffusivity of the sphere. It was found that the properties of the coating have a direct effect on the cooling rate of the sphere.     

Diagnosing attention disorders in a virtual classroom

The virtual classroom provides an efficient and scalable tool for conducting attention testing. The University of Southern California integrated media systems center and digital media works have partnered to develop virtual reality technology applications for the study, assessment, and rehabilitation of cognitive and functional processes. This work primarily focuses on the development of systems that address the special needs of clinical populations with central nervous system dysfunctions such as brain injury, learning disabilities, or neurological disorders.