Blood Transfusions: Are They Life Saving or Transfusing Infections?

Introduction: There is a risk of 1 - 2 per 1000 recipients receiving contaminated blood with viral, bacterial and parasitic agents.TTI’S are the most commonly encountered complications in transfusion medicine. The objective of the study was to determine the seroprevalence of TTI’s among blood donors, who represent healthy population at large. Materials & methods: A total of 33,658 blood units were received from voluntary and replacement donors over a period of 5 years. Surface antigen of HBV and antibodies to HIV and HCV were determined using ELISA. Syphilis was detected using TPHA test. Results: 947 (2.81%) blood units tested positive for HBV, HCV, HIV and / or syphilis. Overall prevalence was HBV – 1.77%, HCV – 0.13%, HIV – 0.63% and Syphilis – 0.28%. Nine (0.03%) donors had coinfections. Conclusion: The screening of blood donors is the corner stone in assuring the safety of blood transfusion

The Enrollment Effects of Merit-Based Financial Aid: Evidence from Georgia's HOPE Scholarship

This paper examines the effects of Georgia's merit-based HOPE Scholarship on college enrollment. Introduced in 1993, the HOPE Scholarship covers tuition, fees, and book expenses for students attending Georgia public colleges, and provides a subsidy of comparable value to students attending in-state private colleges, without any income restrictions. Treating HOPE as a natural experiment, we contrast college enrollment in Georgia with those in the other member states of the Southern Regional Educational Board using IPEDS data for the period 1988-97. We estimate that the HOPE increased total freshmen enrollment by 5.9 percent, with the gains concentrated in 4-year schools. For freshmen recently graduated from high school attending 4-year colleges, two-thirds of the program effect is explained by a decrease in students leaving the state. Both white and black enrollments increased because of HOPE, with the state's historically-black institutions playing an important role. Finally, the total HOPE-induced enrollment increase represents only 15 percent freshmen scholarship recipients.Higher Education, Enrollment, HOPE, Merit-based Aid

Origin of ferromagnetism in Cs2_2AgF4_4: importance of Ag - F covalency

The magnetic nature of Cs$_{2}$AgF$_{4}$, an isoelectronic and isostructural analogue of La$_2$CuO$_4$, is analyzed using density functional calculations. The ground state is found to be ferromagnetic and nearly half metallic. We find strong hybridization of Ag-$d$ and F-$p$ states. Substantial moments reside on the F atoms, which is unusual for the halides and reflects the chemistry of the Ag(II) ions in this compound. This provides the mechanism for ferromagnetism, which we find to be itinerant in character, a result of a Stoner instability enhanced by Hund's coupling on the F

ELM ZA KLASIFIKACIJU TUMORA MOZGA KOD 3D MR SNIMAKA

Extreme Learning machine (ELM) a widely adopted algorithm in machine learning field is proposed for the use of pattern classification model using 3D MRI images for identifying tissue abnormalities in brain histology. The four class classification includes gray matter, white matter, cerebrospinal-fluid and tumor. The 3D MRI assessed by a pathologist indicates the ROI and the images are normalized. Texture features for each of the sub-regions is based on the Run-length Matrix, Co-occurence Matrix, Intensity, Euclidean distance, Gradient vector and neighbourhood statistics. Genetic Algorithm is custom designed to extract and sub-select a decisive optimal bank of features which are then used to model the ELM classifier and best selection of ELM algorithm parameters to handle sparse image data. The algorithm is explored using different activation function and the effect of number of neurons in the hidden layer by using different ratios of the number of features in the training and test data. The ELM classification outperformed in terms of accuracy, sensitivity and specificity as 93.20 %, 91.6 %, and 97.98% for discrimination of brain and pathological tumor tissue classification against state-of-the-art feature extraction methods and classifiers in the literature for publicly available SPL dataset.ELM, široko prihvaćen algoritam strojnog učenja se predlaže za korištenje u uzorkovanju pomoću klasifikacijskog modela 3D MRI slika za identifikaciju abnormalnosti tkiva u histologiji mozga. Četiri klase obuhvaćaju sive, bijele tvari, cerebrospinalne tekućine-i tumore. 3D MRI koji ocjenjuje patolog, ukazuje na ROI, a slike su normalizirane. Značajke tekstura za svaku od podregija se temelje na Run-length matrici, ponovnom pojavljivanju matrice, intenzitet, euklidska udaljenost, gradijent vektora i statistike susjedstva. Genetski algoritam je obično dizajniran za izdvajanje i sub-optimalan odabir odlučujući o značajkama koje se onda koriste za model ELM klasifikatora i najbolji izbor ELM parametra algoritama za obradu rijetkih slikovnih podataka. Algoritam se istražuje koristeći različite aktivacijske funkcije i utjecaj broja neurona u skrivenom sloju pomoću različitih omjera broja značajki kod trening i test podataka. ELM klasifikacija je nadmašila u smislu točnosti, osjetljivosti i specifičnosti, kao 93,20%, 91,6% i 97,98% za diskriminaciju mozga i patološki kod tumora i sistematizacije metode za prikupljanje podataka i klasifikatore u literaturi za javno dostupne SPL skup podataka

Contributions of Sushruta to Anatomy

Sushruta, a practitioner of ancient Indian Medicine has made significant contributions to various branches of medicine. He is glorified as Father of Indian Surgery. He performed surgeries in the era when no diagnostic facilities were available. What astonishes is the favorable outcome from most of his procedures. Probably, the exhaustive knowledge of basic sciences he had would have made him a versatile surgeon. This article has compiled the contributions of this great stalwart to anatomy and interprets his perspective towards teaching this subject.Keywords: Sushruta, Dissection, Cadaver, Anatomy, Preservatio

Parallel Smith-Waterman Algorithm for Gene Sequencing

Smith-Waterman Algorithm represents a highly robust and efficient parallel computing system development for biological gene sequence. The research work here gives a deep understanding and knowledge transfer about exiting approach for gene sequencing and alignment using Smith-waterman their strength and weaknesses. Smith-Waterman algorithm calculates the local alignment of two given sequences used to identify similar RNA, DNA and protein segments. To identify the enhanced local alignments of biological gene pairs Smith-Waterman algorithm uses dynamic programming approach. It is proficient in finding the optimal local alignment considering the given scoring system. DOI: 10.17762/ijritcc2321-8169.150515

Heart rate Encapsulation and Response Tool using Sentiment Analysis

Users of every system expect it to get better. Providing feedback to the owners or management was difficult but with the advent of technology, it has become handy. Users can now post their comments through online blogs, android apps and websites. Due to the enormous data piling up every second causes a problem in analyzing it. In this paper, sentiment analysis is used for analyzing comments and reviews for hospital management system are demonstrated with real time data. The tools, algorithms and methodology that could fetch accurate results is described. Experimental results indicate 90% of accuracy in proposed system. The review report generated would help the hospital management to identify the positive and negative feedback which further assists them in improving their facilities that could not only create customer satisfaction but also enhanced business processes