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A key advantage of Mobile Adhoc Networks is the mobility offered to the users. But the mobility is unpredictable and may cause routes to break frequently. The frequent breaks in routes adversely affect Quality of Service requirement of applications in the mobile wireless networks and thus pose a challenge. In this paper, we have proposed a method for signal strength based link availability prediction to be used in AODV routing. The nodes estimate the link breakage time and further warns the other nodes about the link breaks in the route. Based on this information, either local route repair or new route discovery is initiated much earlier than the route breakage. This reduces the data packet losses as well as end-to-end delay. The proposed approach is compared with AODV without link prediction. The results show that there is significant reduction in packet drops and average end-to-end delay. There is also an improvement in data packet delivery ratio for AODV with link prediction. Proposed approach results in improvement in the Quality of Service.

Polymorphonuclear leukocyte chemiluminescence and chemotaxis assays were performed on cells obtained from normal individuals and patients with defined defects in chemotaxis or chemiluminescence. After in-vitro pre-incubation with trimethoprim/sulphamethoxazole, its separate components, clindamycin and cefotaxime, normal cells showed some enhancement in chemotaxis and significant increase in chemiluminescence. There was an even more marked increase in chemotaxis when these antibiotics were incubated with cells from patients with leukocyte chemotaxic defects. When the cells from patients with chemiluminescence defects were pre-incubated with these antibiotics, there was also substantial enhancement in chemiluminescence.

Background: Microbial pathogens cause human skin and soft tissue infections (SSTI) and surgical site infections (SSI) after surgical procedures. These can result in the production of pus, yellowish fluid comprising of dead WBCs and cellular debris. The microorganisms responsible for pus production vary greatly in relation to their spectrum of prevalence in different hospital and also in their antibiotic sensitivity. Further, the antibiotic sensitivity also changes because of the emergence of resistant strains. It is therefore, important that the common bacterial pathogens causing infection in a particular hospital and their sensitivity should be known. This will help in the choice of prophylactic antibiotic and in initiating the empirical antibiotic prescription for the infected cases before the culture sensitivity report is made available which takes about 2-3 days. Objective: To identify the spectrum of aerobic bacteria which are responsible for SSTI and SSI and their antibiotic sensitivity pattern. Method: This cross sectional hospital based study was conducted in Nepalgunj Medical College and Teaching Hospital (NGMCTH), Kohalpur from January 2019 to November 2019. These pus swabs were obtained from the Department of Surgery and Department of Gynaecology & Obstretics. Samples were cultured in the Microbiology laboratory of NGMCTH, Kohalpur. Identification and characterization of isolates were performed on the basis of Gram staining and cultural characteristics. Antibiotic sensitivity test was performed in vitro by Bauer-Kirby method. Collected data were statistically analyzed using SPSS 20.0 and Microsoft Excel 2015. Results: During the study period, a total number of 311 pus swabs were obtained among which only 164 (52.73%) pus swab showed bacterial growth. Out of 164 pus swabs, 150 pus swabs yielded monomicrobial growth (150 bacterial isolates) and 14 pus swabs yielded polymicrobial growth (33 bacterial isolates). Gram Negative Bacteria (60.1%) was more prevalent than Gram Positive Bacteria (39.9%). Combined together, the most common isolate was S. aureus (36.1%) followed by E.coli (24.0%), Klebsiella (14.2%), Enterobacter (11.5%), Pseudomonas (9.8%), S. pyogenes (3.3%) and Proteus (1.1%). S. aureus was highly sensitive to Doxycycline (90.6%), Chloramphenicol (81.5%), Amikacin (79.5%) and Ceftraixone (72.7%). S. pyogenes showed 100% sensitivity to Cefexime, Amikacin, Chloramphenicol, Azithromycin and 80% sensitivity to Doxycycline. Similarly, most common gram negative isolate E.coli showed higher sensitivity to Chloramphenicol(71.4%) and Amikacin (66.7%) , Klebsiella showed higher sensitivity to Doxycycline(92.3%), Gentamicin(87.5%) and Amikacin (81.0%), Enterobacter showed higher sensitivity to Amikacin(90.9%) and Pseudomonas was highly sensitive to Chloramphenicol (71.4%) and Amikacin (66.7%). Piperacillin, Amikacin, Gentamicin, Ofloxacin and Ceftriaxone showed 100% sensitivity to Proteus spp. Amoxyclav, Cefepime and Cefexime (except in S. pyogenes) showed least sensitivity in both gram negative and gram positive bacterial isolates. Conclusion: In our study, the most common isolate wasS. aureus. Amikacin, as a single drug was found to be effective for empirical therapy of both gram negative and gram positive bacteria whereas Doxycycline and Amikacin was found effective in gram positive isolates. Amoxyclav and Cefepimewas commonly resistant in all bacterial isolates.

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