Bacteriology of Surgical Site Infections after Colorectal surgeries
Surgical Site Infection (SSI) is the infection of the skin and subcutaneous tissues, organs or spaces exposed by surgeons during the performance of an invasive procedure. Appropriate antimicrobial therapy is mandatory not only to improve the prognosis of patients with SSIs but also to minimize the occurrence of antibiotic-resistant organisms. To use antibiotics appropriately, especially before the availability of culture sensitivity reports, information on the prevalent microbial flora isolated from SSIs is of particular value. The purpose of this study was to study the bacteriological spectrum of SSIs in colorectal surgical patients. This 2-year prospective study of 272 patients was conducted in the Department of Colorectal Surgery at a tertiary care hospital in Kashmir. Postoperatively surgical site infected cases were identified using CDC, USA definition for SSI. After discharge from hospital, patients were followed for up to 30 days to check any signs of SSI. If there were no signs of SSI within 30 days of operation, the patient was regarded as having no SSI. After identifying a patient with SSI, puss culture swabs were sent to the microbiology laboratory of the institute. After collecting the reports of swab culture, data was analyzed statistically and inferences were drawn from there. Out of 272 patients, 36 patients developed SSI that is the SSI rate in our series was 13.2%. Incisional SSIs comprised about 89% while as organ/space infections comprise only about 11% of total SSIs in this study. Out of 36 SSI patients, only 24 had positive swab/puss culture reports that are swab/puss culture positivity rate was 66.67%. The most common organism found was Staph aureus followed by E.coli. Gram positive organisms out-numbered the gram negative ones in our study of SSI in colorectal patients. Swab/puss culture positivity rate in our study is 66.67%. The most common organism found in SSI after colorectal surgery is Staphylococus aureus followed by E.coli. Also the gram positive organisms out-numbered the gram negative ones in SSI in colorectal patients.
Published by: Dr. Mudassir Ahmad Khan, Nisar A Chowdri, Dr. Ajaz Ahmad Bhat, Fazl Q Parray, Dr. Asif Mehraj, Dr. Rauf A Wani, Dr. Arshad Baba, Dr. Mushtaq Laway
Author: Dr. Mudassir Ahmad Khan
Paper ID: V4I4-1504
Paper Status: published
Published: August 30, 2018
Using human area networking to enhance Internet of Things and human organ analysis
Internet of Things is a technology that refers to connect anything with internet based on stipulated protocols to produce information using sensing devices, to transfer data which in turn results in better tracking, positioning, monitoring, administration and extraction of optimal usage form All Things around us. In this paper, we use the Redtacton technology to overcome the security and external signal dependency of INTERNET OF THINGS and make it as a more personalized one wherein it’s used for medical application using genetic algorithmic sequences (organ cycle, chakras stimulation).
Published by: Dorothy Joseph E
Author: Dorothy Joseph E
Paper ID: V4I4-1559
Paper Status: published
Published: August 30, 2018
Document clustering using K-Means clustering in Hadoop using Map Reduce
The high dimensional information concerns expansive volume, mind-boggling, mounting informational indexes with various, self-governing sources. As the Data expanding radically every day, it is a noteworthy concern to oversee and compose the information productively. This developed the need for machine learning systems. With the Fast advancement of Networking, information stockpiling and the information gathering limit, Machine learning bunch calculations are presently quickly growing in all science and building spaces, for example, Pattern acknowledgment, information mining, bioinformatics, and proposal frameworks. In order to help the adaptable machine learning system with Map Reduce and Hadoop bolster, we are utilizing YARN Yet Another Resource Negotiator to deal with the High Voluminous information. Different Cluster issues, for example, Cluster propensity, partition, Cluster legitimacy, and Cluster recital canister be effectively overwhelmed by YARN bunching calculations. Mahout oversees information in four stages i.e., bringing information, content mining, bunching, arrangement, and community-oriented separating. In the proposed approach, different information writes, for example, Numbers, Raw Data and 3D-Images however, datasets are arranged in the few classifications i.e., Collaborative Filtering, Clustering, Classification or Frequent Itemset Mining.
Published by: Utkarsh Jaiswal, Kunal Gupta
Author: Utkarsh Jaiswal
Paper ID: V4I4-1526
Paper Status: published
Published: August 29, 2018
Performance based design of RCC structure
The prediction of inelastic seismic responses and the evaluation of seismic performance of a building structure are very important subjects in performance-based seismic design. The seismic performances of reinforced-concrete buildings evaluated by nonlinear static analysis (pushover analysis) and nonlinear time history analysis are compared in this research. A finite element model that can accurately simulate the nonlinear behavior of building is formulated by considering several important effects such as p-delta can be considered rigid zones with joint failure due to the poor detailing of joints. Both global responses such as system ductility demand and local response such as inter-story drift are investigated in this research. A numerical example is performed on a 20-story reinforced concrete building in ZONE V. Finally, the global and local responses obtained from the pushover analysis are compared with those obtained from the nonlinear dynamic analysis of MDOF system. The results show that the PA is accurate enough for practical applications in seismic performance evaluation when compared with the nonlinear dynamic analysis of MDOF system.
Published by: Md. Rehan, Faiyaz Azam
Author: Md. Rehan
Paper ID: V4I4-1548
Paper Status: published
Published: August 29, 2018
Clinicopathological Profile of Gastrointestinal Stromal Tumors
Gastrointestinal stromal tumors (GISTs) are rare tumors of gastrointestinal tract arising from interstitial cells of Cajal. They present with varied clinical features most of which are non- specific. This study was done to identify the clinical features of GISTS and immunohistochemistry. It was a retrospective and prospective study. The total number of studied patients was 50. Out of 50 patients- 26 were females (52%). Mean Age of involvement was 59 years. Gastrointestinal bleeding and Pain abdomen were the most common symptoms. Stomach was involved in 64%, small gut in28% and colon in 4% of the patients. The average size of the tumor was 5.2cm. 96% were CD117 positive. GISTS are rare tumors arising in late middle age. They affect males and females equally. They present non- specific signs and symptoms. Most of them are CD117 positive.
Published by: Rayees A Khanday, Ajaz Malik, Munir Wani, Zubaida Rasool
Author: Rayees A Khanday
Paper ID: V4I4-1541
Paper Status: published
Published: August 29, 2018
Pochhammer symbol of ultra gamma function and its applications to hypergeometric functions
The aim of this paper is to investigate an extension of generalized hypergeometric function rFs with r numerator and s denominator parameters with help of ultra gamma function. Some Recurrence relation of the Pochhammer symbol of Ultra Gamma Function is investigated. Certain particular cases of the derived results are considered and indicated to further reduce to some known results. Finally, we present a systematic study of the various fundamental properties of the class of hypergeometric functions introduced here.
Published by: Anita, K. S. Gehlot, Chena Ram
Author: Anita
Paper ID: V4I4-1553
Paper Status: published
Published: August 29, 2018
