Vaccines: Propaganda and Practice

Vaccines are a cost effective, time tested means of reducing morbidity and mortality. As more and more new vaccines are introduced and more diseases come under the purview of ‘vaccination net’, the routine immunization program is sidelined.\ud This is compounded by vaccination practices in private health care system and anti vaccine propaganda and confusing pro vaccine propaganda. The primary purpose of the vaccine is shifting from prevention of diseases to monetary gains for the health care providers and manufacturers. There is a need to regulate the vaccination practices in the private health care system especially in the developing countries. The regulatory process should educate not only the community but also the health care providers and take adequate measures to control the ‘vaccine market forces

Co-Scheduling Algorithms for High-Throughput Workload Execution

This paper investigates co-scheduling algorithms for processing a set of parallel applications. Instead of executing each application one by one, using a maximum degree of parallelism for each of them, we aim at scheduling several applications concurrently. We partition the original application set into a series of packs, which are executed one by one. A pack comprises several applications, each of them with an assigned number of processors, with the constraint that the total number of processors assigned within a pack does not exceed the maximum number of available processors. The objective is to determine a partition into packs, and an assignment of processors to applications, that minimize the sum of the execution times of the packs. We thoroughly study the complexity of this optimization problem, and propose several heuristics that exhibit very good performance on a variety of workloads, whose application execution times model profiles of parallel scientific codes. We show that co-scheduling leads to to faster workload completion time and to faster response times on average (hence increasing system throughput and saving energy), for significant benefits over traditional scheduling from both the user and system perspectives

Creative Design of a Device that not only Cleans the Teeth but also Anti-Germinates

In the past various methods have been found to clean the teeth but until recently not much importance has been given to the anti-germinating idea. After analyzing the causes of tooth decay the importance of anti-germinating has been found. Now there are various devices available to clean and anti-germinate the teeth but a system that combines both cleaning and anti-germinating has not been produced on a mass scale yet. In this report we first study the history and evolution of cleaning the teeth. Then the various devices and chemicals used today to clean the teeth are analyzed. This is followed by the project analysis. Some designs that could provide a solution for the problem are found. Out of this the best design is found out considering factors like effort required, cost, efficiency, time. The various possible subsystems of the device are listed. The morphological analysis is then done. The most efficient and cost effective combination of subsystems is selected .This is the solution for the problem. The specification and size of the parts of the device is also given

Implementation of Distributed Time Exchange Based Cooperative Forwarding

In this paper, we design and implement time exchange (TE) based cooperative forwarding where nodes use transmission time slots as incentives for relaying. We focus on distributed joint time slot exchange and relay selection in the sum goodput maximization of the overall network. We formulate the design objective as a mixed integer nonlinear programming (MINLP) problem and provide a polynomial time distributed solution of the MINLP. We implement the designed algorithm in the software defined radio enabled USRP nodes of the ORBIT indoor wireless testbed. The ORBIT grid is used as a global control plane for exchange of control information between the USRP nodes. Experimental results suggest that TE can significantly increase the sum goodput of the network. We also demonstrate the performance of a goodput optimization algorithm that is proportionally fair.Comment: Accepted in 2012 Military Communications Conferenc

Co-scheduling algorithms for high-throughput workload execution

International audienceThis paper investigates co-scheduling algorithms for processing a set of parallel applications. Instead of executing each application one by one, using a maximum degree of parallelism for each of them, we aim at scheduling several applications concurrently. We partition the original application set into a series of packs, which are executed one by one. A pack comprises several applications, each of them with an assigned number of processors, with the constraint that the total number of processors assigned within a pack does not exceed the maximum number of available processors. The objective is to determine a partition into packs, and an assignment of processors to applications, that minimize the sum of the execution times of the packs. We thoroughly study the complexity of this optimization problem , and propose several heuristics that exhibit very good performance on a variety of workloads, whose application execution times model profiles of parallel scientific codes. We show that co-scheduling leads to faster workload completion time (40% improvement on average over traditional scheduling) and to faster response times (50% improvement). Hence co-scheduling increases system throughput and saves energy, leading to significant benefits from both the user and system perspectives

Analysis on IoT Challenges, Opportunities, Applications and Communication Models

Internet of Things (IoT) is a novel communication standard and it is researcher's preferred topic, which integrates heterogeneous systems seamlessly. Designing a universal architecture for IoT is a challenging task due to the integration of wide variety of the devices. The main objective of this paper is to provide comprehensive knowledge on challenges, applications, Security issues, and different communication models of IoT. This paper also focuses on the marketing trends of IoT with respect to variety of application with the end users. This motivates the researchers to contribute more productive work in this field by analyzing various parameters

Co-scheduling algorithms for cache-partitioned systems

Cache-partitioned architectures allow subsections of theshared last-level cache (LLC) to be exclusively reserved for someapplications. This technique dramatically limits interactions between applicationsthat are concurrently executing on a multi-core machine. Consider n applications that execute concurrently, with the objective to minimize the makespan, defined as the maximum completion time of the n applications.Key scheduling questions are: (i) which proportionof cache and (ii) how many processors should be given to each application?Here, we assign rational numbers of processors to each application,since they can be shared across applications through multi-threading.In this paper, we provide answers to (i) and (ii) for perfectly parallel applications.Even though the problem is shown to be NP-complete, we give key elements to determinethe subset of applications that should share the LLC(while remaining ones only use their smaller private cache). Building upon these results,we design efficient heuristics for general applications.Extensive simulations demonstrate the usefulness of co-schedulingwhen our efficient cache partitioning strategies are deployed

DMAP: a connectivity map database to enable identification of novel drug repositioning candidates

BACKGROUND: Drug repositioning is a cost-efficient and time-saving process to drug development compared to traditional techniques. A systematic method to drug repositioning is to identify candidate drug's gene expression profiles on target disease models and determine how similar these profiles are to approved drugs. Databases such as the CMAP have been developed recently to help with systematic drug repositioning. METHODS: To overcome the limitation of connectivity maps on data coverage, we constructed a comprehensive in silico drug-protein connectivity map called DMAP, which contains directed drug-to-protein effects and effect scores. The drug-to-protein effect scores are compiled from all database entries between the drug and protein have been previously observed and provide a confidence measure on the quality of such drug-to-protein effects. RESULTS: In DMAP, we have compiled the direct effects between 24,121 PubChem Compound ID (CID), which were mapped from 289,571 chemical entities recognized from public literature, and 5,196 reviewed Uniprot proteins. DMAP compiles a total of 438,004 chemical-to-protein effect relationships. Compared to CMAP, DMAP shows an increase of 221 folds in the number of chemicals and 1.92 fold in the number of ATC codes. Furthermore, by overlapping DMAP chemicals with the approved drugs with known indications from the TTD database and literature, we obtained 982 drugs and 622 diseases; meanwhile, we only obtained 394 drugs with known indication from CMAP. To validate the feasibility of applying new DMAP for systematic drug repositioning, we compared the performance of DMAP and the well-known CMAP database on two popular computational techniques: drug-drug-similarity-based method with leave-one-out validation and Kolmogorov-Smirnov scoring based method. In drug-drug-similarity-based method, the drug repositioning prediction using DMAP achieved an Area-Under-Curve (AUC) score of 0.82, compared with that using CMAP, AUC = 0.64. For Kolmogorov-Smirnov scoring based method, with DMAP, we were able to retrieve several drug indications which could not be retrieved using CMAP. DMAP data can be queried using the existing C2MAP server or downloaded freely at: http://bio.informatics.iupui.edu/cmaps CONCLUSIONS: Reliable measurements of how drug affect disease-related proteins are critical to ongoing drug development in the genome medicine era. We demonstrated that DMAP can help drug development professionals assess drug-to-protein relationship data and improve chances of success for systematic drug repositioning efforts

Evaluation of an Intermittent Six-month Regimen in New Pulmonary Tuberculosis Patients with Diabetes Mellitus

Background: The treatment of tuberculosis (TB) with category I regimen of the Revised National Tuberculosis Control Programme (RNTCP) for patients with diabetes mellitus (DM) needs evaluation. Objective: To assess the cure and relapse rates in 3 years, among the new smear-positive TB patients with Type-2 DM (DMTB) treated with CAT-I regimen (2E3H3R3Z3/4R3H3) of RNTCP. Methodology: TB suspects attending the diabetology units and the TB research centre (TRC) Chennai, were investigated. Eligible DMTB cases were enrolled. Baseline estimation of cardiac, renal, liver function tests and glycosylated-HBA1c were undertaken. All patients received 2E3H3R3Z3/4R3H3 under supervision at TRC. Clinical and sputum (smear and culture) examinations and monitoring of diabetic status were undertaken every month up to 24 months, then once in 3 months up to 36 months. Results: Of 100 patients admitted, 7 were excluded for various reasons from analysis. Of 93 patients, 87 (94%) had a favourable response at the end of treatment. Pre and post treatment mean glycosylated-HBA1c were 9.7% and 8.4 %.(>7% poor control). During follow-up period, 6 died and one lost to follow-up. Of the remaining, four relapsed. Conclusion: Category-I regimen, recommended for all the new smear-positive patients in the Indian TB programme, is effective in the treatment of DMTB patients, despite poor control of diabetes

An Advanced Caching Solution to Cluster Storage Environment

Clustered storage is the deployment of multiple data servers working together to improve reliability, capacity and performance. Clustering divides workloads to every storage server to control and monitor workload transfer and file access between servers without taking into account of the physical location of the file. Solid State Drives (SSD) can be considered as a more sophisticated version of a USB memory stick since the memory stick does not have any moving part associated with it and moreover, data is stored in microchips. In this paper, we give an overview of an advanced caching solution to improve IO and application performance by using flash storage in cluster storage environment. It is a cluster storage solution with two highly scalable servers with optimizations to ensure fast service failovers and deploying one or two solid state drives as the cache devices for faster and better performance. The software supports write-back caching policy where both read and write requests on hot regions of drivesare cached. With write-back, write requests to the hot regions are acknowledged immediately after it is written to the cache device and this (dirty) data will be flushed to back-end virtual drive in the background. Flushing of dirty data will be performed by the flush manager of the software under different scenarios like amount dirty data reaches a threshold, IO activity during a time interval is low etc. The solution effectively harnesses the flash storage performance potential by retaining only frequently accessed data in flash for quick retrieval. The solution provides unmatched efficiency, performance, support and reliability for enterprises or storage world