Comment: The Role of Happenstance in Multidisciplinary Education

Notwithstanding a successful experience in interdisciplinary education at Cornell, Dr. Heath has found that students interested in multidisciplinary education confront an ever-shifting mosaic of opportunity. Thus, the author believes that success is apt to be more a matter of serendipity than careful planning

Modelling efficiency with farm-produced inputs: dairying in KwaZulu-Natal, South Africa

This paper models dairy farms in KwaZulu-Natal, South Africa, emphasising the complexities unique to this multi-product industry. Net and gross output approaches to measuring production are discussed and then tested using panel data from 37 dairy farms in KwaZulu-Natal from 1999 and 2007. Production functions for the three outputs: milk production, animals and farm-produced feed, are fitted as a simultaneous system to model the farms’ production activities. This simultaneous model is complemented by a single equation reduced form that is fitted as a frontier, which allows estimation of the relative efficiencies of the individual farms. The results show that, with data this detailed, it is possible to refine the model until it fits very tightly. Indeed, in the gross output model that includes cows there is nothing left to call inefficiency and what was clearly a frontier becomes a mean response function.Dairy farms, production, frontiers, efficiency, Production Economics,

Performance Analysis of a new Filter and Wrapper Sequence for the Survivability Prediction of Breast Cancer Patients

Feature selection is an essential preprocessing step for removing redundant or irrelevant features from multidimensional data to improve predictive performance. Currently, medical clinical datasets are increasingly large and multidimensional and not every feature helps in the necessary predictions. So, feature selection techniques are used to determine relevant feature set that can improve the performance of a learning algorithm. This study presents a performance analysis of a new filter and wrapper sequence involving the intersection of filter methods, Mutual Information and Chi-Square followed by one of the wrapper methods: Sequential Forward Selection and Sequential Backward Selection to obtain a more informative feature set for improved prediction of the survivability of breast cancer patients from the clinical breast cancer dataset, SEER. The improvement in performance due to this filter and wrapper sequence in terms of Accuracy, False Positive Rate, False Negative Rate and Area under the Receiver Operating Characteristics curve is tested using the Machine learning algorithms: Logistic Regression, K-Nearest Neighbour, Decision Tree, Random Forest, Support Vector Machine and Multilayer Perceptron. The performance analysis supports the Sequential Backward Selection of the new filter and wrapper sequence over Sequential Forward Selection for the SEER dataset

Opening the flow of citizen engagement: An exploratory study of social networking services as a potential vehicle for e-participation in the City and County of Honolulu

Peer-reviewed journal articleThis study examined the use of Social Networking Services (SNS) by policymakers in the City and County of Honolulu. Interviews identified policymakers’ main reasons for using SNS, examined how SNS was integrated into the policymaking process, and also highlighted issues faced in deploying SNS for government services. The City and County informally initiated use of SNS in 2008, and use remained at an early stage of integration into business processes and operations at the time of this study. Government-operated SNS was primarily used as a one-way-information-based service. In this early stage, SNS was not being used to directly promote e-participation initiatives, although potential future uses were discussed. Government officials noted a spectrum of desired expectations regarding future development of SNS. We recommend an agency-wide use policy be created to provide for consistency of use across administrations and that a formal pilot study, addressing the perspectives of multiple stakeholders, be initiated

HIV-2 Reverse Transcriptase using Chemical Similarity Process of Reducing Viral Attack and Increasing CD4 Counts in HIV-Infected Patients

The aim of this study is to examine the Chemical processes focused to reduce viral attack and increasing CD4 counts, HIV viral load after initiation of combination antiretroviral treatment. However by purchasing and assaying of selected top-scoring compounds from the library active anti-HIV agents are created. Subsequent synthesis and assaying of S10087 analogs proposed by further computational analysis yielded anti- HIV agents. Thus, with the aid of computational tools, it was possible to evolve a false positive into a true active. Antiretroviral treatment–naive, chronically HIV-infected persons (n = 1376 and n = 1605 for each of the 2 cohorts) are untreated. During the observation period (5 months), at least 1 HIV RNA level and 2 CD4 cell counts may be stable. Approximately 35% were nonwhite, and 45% had risk factors. Currently, the data would generally support initiation of HAART in patients with CD4 cell counts more than 350 cells/µl. However, from the strong potential for confounding in observational studies and the lack of adjustment for lead-time bias in many analyses, it is not possible to rule out possible long-term detrimental effects of earlier use of HAART. In chemical process we can use these chemicals and it is possible to reduce the critical bond in HIV virus and increase the amount of CD 4 counts

ANTIDIABETIC AND ANTIOXIDANT EFFICACY OF BONE MARROW STEM CELLS ON STZE-INDUCED MALE ALBINO WISTAR RATS

Diabetes mellitus is a multi-metabolic disorder that influences more than 348 million people worldwide. A key goal of diabetes treatment is to prevent complications because over time, diabetes can damage the heart, blood vessels, eyes, kidneys, and nerves. Consequently there is an incredible need to develop new and successful therapies for treating diabetic complications early before it causes irreparable tissue damage. Bone marrow derived mesenchymal stem cells (BMSCs) offer significant benefits for clinical application, because they can be easily harvested and, when autologous transplanted, there is no immunological rejection. Moreover, BMSCs can differentiate into a wide variety of cell types. Here, we focused on bone marrow-derived mesenchymal stem cells (MSCs) can transdifferentiate into insulin-producing cells (IPC) under defined conditions  and normalize the glucose level of streptozotocin (STZ)- induced diabetic rats.The main objective of  the study was To evaluate the antidiabetic activity of the Dental pulp cells in Streptozotocin (STZ)-induced diabetic Wistar albino rats.To calculate the biochemical estimation of both normal and treated groups.To study the effects of dental pulp cells on morphological characterization of normal and treated groups. Streptozotocin.,Wistar albino rat.,Insulin.,stem cell.,fibroblas

Analysis and Exploration of Novel Antibiotic-Producing Streptomyces spp. in Spokane County, Washington

According to the Centers for Disease Control and Prevention, a US citizen is infected by an antibiotic-resistant pathogen every 11 seconds, and every 15 minutes, a patient dies as a result of these infections. Due to the increasing incidence of antibiotic-resistant pathogenic microbes, the study and exploration of novel antibiotics from novel environments are imperative as infectious diseases are the second leading cause of death in the United States. The purpose of this research is to investigate and analyze antibiotic-producing soil microbes in Spokane County, WA, with hopes of discovering novel antibiotic-producing microbes, specifically Streptomyces species, and explore some of the variables that influence the production of secondary metabolites. My hypotheses are as follows: Soil microbes existing in Spokane County will include Streptomyces spp. capable of producing secondary metabolites suitable to combat selected Gram-negative or Gram-positive bacterial ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumonia, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) and pathogenic fungi such as Candida albicans. Additionally, modifying laboratory variables such as incubation temperature, time in incubation, and the type of media will influence the production of metabolites produced by Streptomyces isolates. Modifying these variables will impact the inhibitory capabilities of these isolates against Gram-negative, Gram-positive, and pathogenic fungal microbes. Cell-free supernatants of secondary metabolites on disk diffusion and 96 well plate assays will be utilized to measure zones of inhibition and inhibitory capabilities with absorbance measured at 600nm using a spectrophotometer