Functional outcome in displaced proximal humeral fractures in adults treated by proximal humeral locking plates

Background: The management of proximal humerus fractures (PHF) is a challenging task to any surgeon. Study was conducted to evaluate the clinical and functional outcome of the proximal humeral internal locking system in fixation of displaced proximal humeral fractures.Methods: Study was conducted in the Department of Orthopedics, GSL Medical College. Informed written consent was taken from the study participants. All skeletally mature patients aged >18 years, presenting with displaced PHF according to Neer two, three and four part fracture were included in the study. Either deltopectoral or deltoid splitting approach was used for surgery, post-operative rehabilitation was started on day one.Results: Twenty-five patients with PHF were enrolled in the study; five-holed proximal humerus locking plate (PHLP) was used for 18 patients, eight-holed PHLP for 05 and three-holed, ten-holed PHLP for 01 for one each. The Constant-Murley score was significantly improved (p=0.000) over each successive follow-up period with the average improvement of around 19 scores between 1st and 2nd follow-up and around 15 score improvement between 2nd and 3rd follow-up.Conclusions: The proximal humeral locking plate is an adequate device for the fixation of displaced two-part, three-part and four-part PHF. Patient can regain good shoulder function, resume normal activities much earlier

Personalization and Location-based Technologies for E-Commerce Applications

Tailoring web-pages to different user characteristics such as location, preferences and previous history (page-hits, products bought) have been shown to be effective tools for personalizing web-content. In this paper, we briefly summarize the techniques in these state-of-the-art personalization technologies. We first describe personalization using user preferences or history and then describe personalization based on user's current location. Whereas the former is applicable for deployment in web-sites, the latter is useful in providing location-based content to mobile users and wireless applications

Efficient Dynamic Range Searching using Data Replication

Given the lower bound of\Omega\Gamma n (d\Gamma1)=d ) for range query time complexity on n d-dimensional point data, we investigate whether little replication can improve the query and update times significantly. We propose linear-space index structures that minimize the query and update times; the query time we achieve is O(n ffl ) for any ffl ? 0, and, the update time is O(log n). 1 Introduction Given a set S of d-dimensional points, a range query q is specified by d 1-dimensional intervals [a i ; b i ] one for each dimension i, and retrieves all points p = (p 1 ; p 2 ; : : : p d ) in S such that h8i 2 f1; : : : ; dg : a i p i b i i. This type of searching in multiple dimensions is fundamental to geographic information systems, image databases and computer graphics. Several efficient data structures using linear and nonlinear space (measured in terms of the number of data points) have been proposed in the literature [Bentley 1977, Bentley 1980, Guttman 1984]. For large databa..

Improved concurrency control techniques for multi-dimensional index structures

Multi-dimensional index structures such as R-trees enable fast searching in high-dimensional spaces. They differ from uni-dimensional structures in the following aspects: (1) index regions in the tree may be modified during ordinary insert and delete operations, and (2) node splits during inserts are quite expensive. Both these characteristics may lead to reduced concurrency of update and query operations. In this paper, we examine how to achieve high concurrency for multi-dimensional structures. First, we develop a new technique for efficiently handling index region modifications. Then, we extend it to reduce/eliminate query blocking overheads during node-splits. We examine two variants of this extended scheme – one that reduces the blocking overhead for queries, and another that completely eliminates it. Experiments on image data on a shared-memory multiprocessor show that these schemes achieve up to 2 times higher throughput than existing techniques, and scale well with the number of processors.

Liver function test abnormalities: Do they correlate with severity in dengue infection? An Indian perspective

Introduction: Involvement of the liver is frequently reported among patients with dengue infection, and liver enzymes are commonly deranged in dengue infection. Raised levels of alanine aminotransferase (ALT) in dengue infection were linked to worse outcomes. The present study was an attempt to study the liver function test abnormalities in dengue fever (DF) and its correlation with the severity of the disease. Methods: The present study was undertaken as a hospital-based retrospective study of DF patients in the age group of 15–60 years. Five hundred and thirty patients who met the eligibility criteria and were admitted to the study hospital during the duration of data collection period (July 2018 to July 2021), comprised the study sample. Differences in means were tested using ANOVA or Kruskal–Wallis test. The difference in proportions was tested using the Chi-square test. Results: Majority of the patients were males (73.4%) with a mean of 30.3 ± 9.7 years. A significant association was observed between clinical features of jaundice, hepatomegaly, splenomegaly, ascites, effusion, bleeding, organ failure, and severe forms of DF. There was a significant positive correlation between aspartate aminotransferase, ALT, and serum bilirubin values among patients with severe forms of DF. Conclusion: Significant proportions of patients with DF without warning signs and severe DF had deranged liver function parameters. A statistically significant association was observed between liver function parameters and the severity of dengue disease

Dimensionality Reduction for Similarity Searching in Dynamic Databases

Databases are increasingly being used to store multi-media objects such as maps, images, audio and video. Storage and retrieval of these objects is accomplished using multi-dimensional index structures such as R -trees and SS-trees. As dimensionality increases, query performance in these index structures degrades. This phenomenon, generally referred to as the dimensionality curse, can be circumvented by reducing the dimensionality of the data. Such a reduction is however accompanied by a loss of precision of query results. Current techniques such as QBIC use SVD transform-based dimensionality reduction to ensure high query precision. The drawback of this approach is that SVD is expensive to compute, and therefore not readily applicable to dynamic databases. In this paper, we propose novel techniques for performing SVD-based dimensionality reduction in dynamic databases. When the data distribution changes considerably so as to degrade query precision, we recompute the SVD transform a..

Dimensionality Reduction for Similarity Searching in Dynamic Databases

Databases are increasingly being used to store multi-media objects such as maps, images, audio and video. Storage and retrieval of these objects is accomplished using multi-dimensional index structures such as R ¢-trees and SS-trees. As dimensionality increases, query performance in these index structures degrades. This phenomenon, generally referred to as the dimensionality curse, can be circumvented by reducing the dimensionality of the data. Such a reduction is however accompanied by a loss of precision of query results. Current techniques such as QBIC use SVD transform-based dimensionality reduction to ensure high query precision. The drawback of this approach is that SVD is expensive to compute, and therefore not readily applicable to dynamic databases. In this paper, we propose novel techniques for performing SVD-based dimensionality reduction in dynamic databases. When the data distribution changes considerably so as to degrade query precision, we recompute the SVD transform and incorporate it in the existing index structure. For recomputing the SVD-transform, we propose a novel technique that uses aggregate data from the existing index rather than the entire data. This technique reduces the SVD-computation time without compromising query precision. We then explore efficient ways to incorporate the recomputed SVD-transform in the existing index structure without degrading subsequent query response times. These techniques reduce the computation time by a factor of 20 in experiments on color and texture image vectors. The error due to approximate computation of SVD is less than 10%.