Co-Tier Interference Reduction with Intelligent Scheduling in between LTE Femtocells

In wireless networks, there is an ever-increasing demand for higher system throughput along with growing expectation for all users to be available to multimedia and Internet services. This is especially difficult to maintain at the cell-edge. To deal with the increasing demand of high speed data streaming and good quality voice traffic from mobile users at home, Femtocell Networks are deployed in homes that enables an indoor mobile user to achieve high speed downloading from the internet and make good quality voice calls. Femtocell networks suffer from the problem of interference. In this paper, a contribution to the existing research on the avoidance of interference in Femtocell networks is presented. The proposed methodology designs a resource allocation and reuse mechanism combined with allocating different resource blocks and interference-aware reuse. The presented results show that the proposed methodology can efficiently mitigate the Co-tier as well as Cross-tier interference in LTE based cellular networks and outperform the other mechanism. DOI: 10.17762/ijritcc2321-8169.150516

Differentiating lymphovascular invasion from retraction artifact on histological specimen of breast carcinoma and their implications on prognosis.

On a pathological specimen of breast cancer cells, retraction artifact during histological processing mimics true lymphovascular invasion (LVI). The accurate determination of the presence or absence of LVI is a factor in determining risk of having a positive sentinel node, or having additional positive axillary nodes after a positive sentinel node biopsy in women with early-stage breast cancer. The determination of nodal risk influences the decision of the treating physicians as to whether a sentinel node biopsy or completion axillary dissection is necessary. On slide preparation, ideal factors favoring true LVI include: a definite endothelial lining, with endothelial nuclei that seem to protrude into the lymphatic space; invasion in one lymphatic vessel (LV) lumen with nearby cancer glands that have minimal or no retraction; a tumor embolus in a LV clear lumen with outside nearby tumor bulk; a tumor embolus that is different in shape than its surrounding clear LV space; and a positive stain for fibrin, CD31, or CD34 on tumor embolus periphery

Evaluation of bioanalyzers for upstream commercial manufacturing

The analyzer currently in use in one of our commercial manufacturing sites for measurement of pH, gases, metabolites and electrolytes during cell culture requires lengthy troubleshooting and excessive maintenance. This has led to loss of operator time and occasional disruption of manufacturing activities. The objective of this study was to replace the current membrane-based analyzer with a more reliable instrument. Two options were evaluated in an effort to reduce maintenance frequency and to minimize operator time spent troubleshooting. Option 1 was to employ a new generation, fully-automated membrane-based analyzer of the same type as the ones currently in place in the manufacturing suite. Option 2 was to employ a combination of a pH/gas analyzer and an absorption/photometric-based metabolite/electrolyte analyzer. Comparability between options 1 and 2 and the analyzer currently in use at the manufacturing site was assessed in the laboratory using quality control standards and bioreactor samples from several commercial cell culture processes. Additionally, operational reliability and robustness of each option relative to the current analyzer as well as fit of the proposed analyzer options with other analyzers in place in commercial BMS facilities were taken into consideration. A summary of the advantages and pitfalls of each option to substitute the current analyzer in the context of a commercial manufacturing facility will be provided

PROTECTIVE EFFECT OF NEBIVOLOL ON ALUMINIUM-INDUCED NEUROBEHAVIORAL AND BIOCHEMICAL ALTERATIONS IN RATS

Objective: The present study was designed to investigate the neuroprotective potential of nebivolol, a β1 adrenergic blocker on aluminium-induced neurobehavioral and biochemical alterations in rats. Methods: The neurotoxicity was induced by administration of aluminium (50 mg/kg/day, p.o.) for 5 weeks. Nebivolol was administered at a dose of 10 mg/kg, p.o. for 5 weeks. Behavioral assessments were done by using open field test and modified elevated plus maze (mEPM) test. At the end of the study, oxidative stress parameters were determined and histopathological studies of cerebral cortex of rat brains were performed. Results: Aluminium chloride treated rats showed significant reduction in motor activity in open field test and memory impairment in mEPM test as compared to control group. Nebivolol significantly reversed these parameters and restored brain antioxidant defensive enzymes with reduction in lipid peroxidation. The neurotoxicity was confirmed by the histopathological analysis of cerebral cortex of rat brains. Aluminium treated animals showed presence of ghost cells, vacuolated cytoplasm and haemorrhage in rat cerebral cortex, indicating neurotoxicity. Nebivolol attenuated all these changes. Thus, the potential of nebivolol to prevent aluminium-induced neurotoxicity was also reflected at microscopic level, indicative of its neuroprotective effects. Conclusion: Nebivolol showed significant antioxidant and neuroprotective activities against aluminium-induced neuronal degeneration. The results of the present study strengthen oxidative stress hypothesis of aluminium-induced neurotoxicity and suggest beneficial role of nebivolol in the treatment of neurodegenerative disorders

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Spray Overlap and Heat Transfer Coefficient Uniformity in Continuous Casting

Continuous casting is an efficient method of producing large volumes of semi-finished steel products. Uniform and efficient heat removal is required to ensure the steel is produced without any cracks while meeting the high steel production target. One of the challenges in the continuous casting process is providing uniform spray cooling rate as needed based on the casting production rate. Improved control of steel cooling rate is critical. The heat removal rate is dependent on the spray nozzle configurations (nozzle spray angle, distance between spray nozzles, nozzle stand-off distance, and water flow rate). The objective of this study is to analyze spray cooling for two nozzles with overlapping sprays. The Lagrangian approach is adopted to track the droplets. In order to predict the slab cooling accurately in the overlap region, droplet breakup and collision are included in the model. The effects of different spray overlap region sizes on the heat transfer coefficient are evaluated by changing the nozzle-to-nozzle distance. The results show that there is an optimum size of spray overlap which provides uniform heat transfer between the two adjacent nozzles. Further increase of the overlap increases heat transfers in the overlap region, which could lead to overcooling of the slab

Artificial neural networks for cardiovascular risk, cardiovascular fitness and ankle-brachial index

Artificial Neural Networks are biologically inspired computational methodologies that can perfom multifactorial analyses. In recent years, they have been evaluated for medical decision support, with varying degrees of success. The preliminary part of my thesis deals with evaluating whether an Artificial Neural Network can be trained to approximate a cardiovascular risk stratification algorithm by Rifai et al. My subsequent work involves training the network on a population-based cross-sectional dataset with the objective of categorizing Ankle-Brachial Index and Maximal Oxygen Consumption. These are indicators of the severity of lower extremity atherosclerosis and the level of cardiovascular fitness respectively. NeuralSIM®, a commercially available Artificial Neural Network, was trained using C-reactive protein and Total Cholesterol/HDL Cholesterol ratio as input parameters, and the relative risk stratum for future myocardial infarctions or stroke as output. For the Ankle-Brachial Index and the cardiovascular fitness networks, data was obtained from the National Health and Nutrition Examination Survey. The network for cardiovascular fitness was compared with an algorithm published by Jackson et al. The network was able to approximate the cardiovascular risk stratification algorithm by Rifai et al closely with correlation coefficients of0.95 in men and 0.93 in women respectively. The network to screen for low cardiovascular fitness had a sensitivity of 83% and a specificity of 78%, with an overall accuracy of 81%. The Ankle-Brachial Index network demonstrated a high level of specificity (86.3%) for estimating abnonnal values but a very low sensitivity (30%). Artificial neural networks showed encouraging results for potential use as decision-support tools. One significant limitation is that the importance of individual parameters or the exact function cannot be ascertained easily. There is a need to address this issue in future software development

Artificial neural networks for cardiovascular risk, cardiovascular fitness and ankle-brachial index

Artificial Neural Networks are biologically inspired computational methodologies that can perfom multifactorial analyses. In recent years, they have been evaluated for medical decision support, with varying degrees of success. The preliminary part of my thesis deals with evaluating whether an Artificial Neural Network can be trained to approximate a cardiovascular risk stratification algorithm by Rifai et al. My subsequent work involves training the network on a population-based cross-sectional dataset with the objective of categorizing Ankle-Brachial Index and Maximal Oxygen Consumption. These are indicators of the severity of lower extremity atherosclerosis and the level of cardiovascular fitness respectively. NeuralSIM®, a commercially available Artificial Neural Network, was trained using C-reactive protein and Total Cholesterol/HDL Cholesterol ratio as input parameters, and the relative risk stratum for future myocardial infarctions or stroke as output. For the Ankle-Brachial Index and the cardiovascular fitness networks, data was obtained from the National Health and Nutrition Examination Survey. The network for cardiovascular fitness was compared with an algorithm published by Jackson et al. The network was able to approximate the cardiovascular risk stratification algorithm by Rifai et al closely with correlation coefficients of0.95 in men and 0.93 in women respectively. The network to screen for low cardiovascular fitness had a sensitivity of 83% and a specificity of 78%, with an overall accuracy of 81%. The Ankle-Brachial Index network demonstrated a high level of specificity (86.3%) for estimating abnonnal values but a very low sensitivity (30%). Artificial neural networks showed encouraging results for potential use as decision-support tools. One significant limitation is that the importance of individual parameters or the exact function cannot be ascertained easily. There is a need to address this issue in future software development

Artificial neural networks for cardiovascular risk, cardiovascular fitness and ankle-brachial index

Artificial Neural Networks are biologically inspired computational methodologies that can perfom multifactorial analyses. In recent years, they have been evaluated for medical decision support, with varying degrees of success. The preliminary part of my thesis deals with evaluating whether an Artificial Neural Network can be trained to approximate a cardiovascular risk stratification algorithm by Rifai et al. My subsequent work involves training the network on a population-based cross-sectional dataset with the objective of categorizing Ankle-Brachial Index and Maximal Oxygen Consumption. These are indicators of the severity of lower extremity atherosclerosis and the level of cardiovascular fitness respectively. NeuralSIM®, a commercially available Artificial Neural Network, was trained using C-reactive protein and Total Cholesterol/HDL Cholesterol ratio as input parameters, and the relative risk stratum for future myocardial infarctions or stroke as output. For the Ankle-Brachial Index and the cardiovascular fitness networks, data was obtained from the National Health and Nutrition Examination Survey. The network for cardiovascular fitness was compared with an algorithm published by Jackson et al. The network was able to approximate the cardiovascular risk stratification algorithm by Rifai et al closely with correlation coefficients of0.95 in men and 0.93 in women respectively. The network to screen for low cardiovascular fitness had a sensitivity of 83% and a specificity of 78%, with an overall accuracy of 81%. The Ankle-Brachial Index network demonstrated a high level of specificity (86.3%) for estimating abnonnal values but a very low sensitivity (30%). Artificial neural networks showed encouraging results for potential use as decision-support tools. One significant limitation is that the importance of individual parameters or the exact function cannot be ascertained easily. There is a need to address this issue in future software development

OVERVIEW ON MICRO MACHINING

In recent years, advanced materials with distinctive metallurgic properties like super alloys, composites and ceramics has been developed to satisfy the strain of maximum applications. whereas these materials square measure more durable, tougher, less heat sensitive and bit more resistant to corrosion and fatigue, they're additionally troublesome to machine.Micro systems can be used in wide applications in biomedical electronics, optics, micro-mechanics, microfluidics, dies, moulds etc. element components employed in these systems have feature dimensions in micrometers and part volumes less than 1 mm3. Manufacture of these parts with high accuracy could be a challenge