Stem cell transplantation in India

This paper outlines the BMT activity in India and describes in some detail the transplant program at the Christian Medical College, Vellore. In September 2005, data from six transplant centers in India were collected and a total of 1540 transplants have been performed in a country of over one billion population. At the center in Vellore, from October 1986 to December 2006, a total of 626 transplants have been performed in 595 patients, with 28 patients having more than one transplant. Thalassemia accounted for a third of these transplants: the country has over 20 million carriers and 10?000 children are born each year with thalassemia major. The average cost of allogeneic BMT in India is around $15000-20000, and this is considerably lower than the cost in the West. India needs to develop more transplant centers with adequately trained personnel, as there is great need for them. Improvements in the economy mean that more patients can afford this treatment

The MVA Priority Approximation

A Mean Value Analysis (MVA) approximation is presented for computing the average performance measures of closed-, open-, and mixed-type multiclass queuing networks containing Preemptive Resume (PR) and nonpreemptive Head-Of-Line (HOL) priority service centers. The approximation has essentially the same storage and computational requirements as MVA, thus allowing computationally efficient solutions of large priority queuing networks. The accuracy of the MVA approximation is systematically investigated and presented. It is shown that the approximation can compute the average performance measures of priority networks to within an accuracy of 5 percent for a large range of network parameter values. Accuracy of the method is shown to be superior to that of Sevcik's shadow approximation

Snapshot Processing in Streaming Environments

Computational issues related to streaming data, and in particular the monitoring and rapid correlation of multiple sources of streaming data, are becoming increasingly important in contexts ranging from business processes to crisis detection. For example, a government system to detect bioterror attacks must correlate multiple streams of possibly low-confidence data from sensors and local and national public health information networks with cues from indicators such as news and government sources indicating geographical locations, tactics and timing of possible attacks. The results of this correlation trigger appropriate responses, such as flagging information for more in-depth analysis or sending alerts to public health officials. Monitoring and correlation applications of this type are ideal for deployment on distributed computing grids, because they have high transaction throughput, require low latency, and can be partitioned into sets of small communicating computations with regular communication patterns. An important consideration in these applications is the need to ensure that, at any given time, computations are carried out on an accurate - or at least close to accurate - picture of the environment being monitored. One way of doing this, which we call snapshot processing, is to treat collections of events that occur at approximately the same time as representing a global snapshot - a valid state - of the environment. Computation on the resulting series of snapshots is much like computation on a real-time video of the entire environment. We briefly describe our model for these stream processing computations and introduce the concept of snapshot processin

IMPLIKASI PROGRAM CSR BANK TERHADAP PEMBERDAYAAN MASYARAKAT DI KOTA KUPANG

The purpose of this study is to analyze the implications of the Corporate Social Responsibility program of Indonesian Reserve Bank on community empowerment in the Sehati and Noetnana clusters of Fatukoa Village, Kupang City. This study uses a qualitative descriptive approach. In this study use SWOT analysis includes efforts to identify strengths, weaknesses, opportunities, and threats that determine company performance. The results from the SWOT analysis that the implementation of cluster development towards community empowerment showed that the cluster had more dominant strengths and opportunities so that it had a positive impact on cluster development, especially the empowerment of the community members of the cluster. Keyword :Klaster Sehati, Klaster Noetnana, CSR (Corporate Social Responsibility

Who shares and who doesn't? Results of the UK Sharing Economy Consumer Survey 2017

The survey, which was conducted in July 2017, captures 1220 responses, and is based on a representative sample of UK population based on gender, income level, education level, and place of residence in the UK. It was structured to ask questions about informants’ current usage of, opinions about, and future intentions to use the following sharing categories: places to stay (e.g. Airbnb, Beds on Board), rides (e.g. Uber, Liftshare), rental cars (e.g. Easycar, Zipcar), parking (e.g. JustPark, Your Parking Space), services (e.g. Parcelly, TaskRabbit), meals (e.g. MealSharing, Eatwith), pre-owned goods (e.g. eBay, Gumtree) and funding (e.g. Justgiving, Crowdcube)

UC: a language for the connection machine

n designing parallel languages, the concern for defining a simple virtual machine must be balanced against the need to efficiently map a program on a specific architecture. UC addresses this problem by separating the programming task from efficiency considerations. UC programs are designed using a small set of constructs that include reduction, parallel assignment, and fixed-point computation. The language also provides a map section that may optionally be used by a programmer to specify data mappings for the program. The authors describe the UC constructs and their implementation on the Connection Machine. They also present measurements of the compiler for simple benchmarks

HYALURONAN-A NOVEL POLYMER ISOLATED FROM MUTATED CLINICAL BACTERIAL ISOLATE

Objective: This study was done to optimize the production parameters involved in the isolation of hyaluronan (HA) from UV mutated a clinical strain of Klebsiella pneumonia (M 3020).Methods: Glucose and nitrogen enriched media (D-glucose, L-glutamic acid, and peptone) were utilized to cultivate the clinical isolate K. pneumoniae. The strain was Ultra Violet (UV) radiation mutated (254 nm, 25 min) and HA production was optimized by parameters such as pH and temperature. The isolated HA from the fermented broth was subjected to purification by isopropyl alcohol and silica gel and further dried by lyophilization. Produced HA was confirmed with UV and Fourier Transform Infra-Red (FT-IR) spectroscopy.Results: UV treated strain at 254 nm for 25 min predominantly produce a high quantity of HA (3.5 g/l) in 37 °C, 300 rpm and pH 6.8 at 24 h run. UV and IR spectrum of produced HA showed strong similarity with the standard hyaluronan.Conclusion: To conclude, high quantity and quality of HA can be isolated from mutated clinical strains of K. pneumoniae

A parallel algorithm for correlating event streams

This paper describes a parallel algorithm for correlating or “fusing” streams of data from sensors and other sources of information. The algorithm is useful for applications where composite conditions over multiple data streams must be detected rapidly, such as intrusion detection or crisis management. The implementation of this algorithm on a multithreaded system and the performance of this implementation are also briefly described

Enterprise Computing Systems as Information Factories

The analysis, and eventual approval or rejection, of new enterprise information technology (IT) initiatives often proceeds on the basis of informal estimates of return on investment. Investment in new IT initiatives includes the costs of hardware, software licenses, application development tailored to the enterprise, and maintenance. Returns are typically estimated informally in terms of cost savings or revenue increases. This paper makes the case for evaluating certain IT investments in the same way as investments in factories and other resources have been evaluated for decades. Just as industrial factories create value by transforming raw materials into finished products, some IT investments, which we call “information factories”, create value by transforming raw information (events) into structured data (and possibly actions based on that data). The return on investment is estimated by the difference between the economic value of the structured data and concomitant actions (the “finished product”) and that of the data available within the enterprise, from its partners and customers, and from the Internet (the “raw materials”). This paper introduces the concept of the information factory, and explores design considerations for maximizing the economic efficiency of information factories