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JOURNAL OF INTEGRATED OMICS A METHODOLOGICAL JOURNAL Environmental OMICS: Current Status and Future Directions
No full textAbstract Objectives: Applications of OMICS to high throughput studies of changes of genes, RNAs, proteins, metabolites, and their associated functions in cells or organisms exposed to environmental chemicals has led to the emergence of a very active research field: environmental OM-ICS. This developing field holds an important key for improving the scientific basis for understanding the potential impacts of environmental chemicals on both health and the environment. Here we describe the state of environmental OMICS with an emphasis on its recent accomplishments and its problems and potential solutions to facilitate the incorporation of OMICS into mainstream environmental and health research. Data sources: We reviewed relevant and recently published studies on the applicability and usefulness of OMICS technologies to the identification of toxicity pathways, mechanisms, and biomarkers of environmental chemicals for environmental and health risk monitoring and assessment, including recent presentations and discussions on these issues at The First International Conference on Environmental OMICS (ICEO), held in Guangzhou, China during November 8-12, 2011. This paper summarizes our review. Synthesis: Environmental OMICS aims to take advantage of powerful genomics, transcriptomics, proteomics, and metabolomics tools to identify novel toxicity pathways/signatures/biomarkers so as to better understand toxicity mechanisms/modes of action, to identify/ categorize/prioritize/screen environmental chemicals, and to monitor and predict the risks associated with exposure to environmental chemicals on human health and the environment. To improve the field, some lessons learned from previous studies need to be summarized, a research agenda and guidelines for future studies need to be established, and a focus for the field needs to be developed. Conclusions: OMICS technologies for identification of RNA, protein, and metabolic profiles and endpoints have already significantly improved our understanding of how environmental chemicals affect our ecosystem and human health. OMICS breakthroughs are empowering the fields of environmental toxicology, chemical toxicity characterization, and health risk assessment. However, environmental OMICS is still in the data generation and collection stage. Important data gaps in linking and/or integrating toxicity data with OMICS endpoints/profiles need to be filled to enable understanding of the potential impacts of chemicals on human health and the environment. It is expected that future environmental OMICS will focus more on real environmental issues and challenges such as the characterization of chemical mixture toxicity, the identification of environmental and health biomarkers, and the development of innovative environmental OMICS approaches and assays. These innovative approaches and assays will inform chemical toxicity testing and prediction, ecological and health risk monitoring and assessment, and natural resource utilization in ways that maintain human health and protects the environment in a sustainable manner
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No full textCloud Computing for Chemical Activity Prediction
Get PDFAbstract-This paper describes how cloud computing has been used to reduce the time taken to generate chemical activity models from years to weeks. Chemists use Quantitative Structure-Activity Relationship (QSAR) models to predict the activity of molecules. Existing Discovery Bus software builds these models automatically from datasets containing known molecular activities, using a "panel of experts" algorithm. Newly available datasets offer the prospect of generating a large number of significantly better models, but the Discovery Bus would have taken over 5 years to compute them. Fortunately, we show that the "panel of experts" algorithm is well-matched to clouds. In the paper we describe the design of a scalable, Windows Azure based infrastructure for the panel of experts pattern. We present the results of a run in which up to 100 Azure nodes were used to generate results from the new datasets in 3 weeks
INFINITE SPEED OF SUPPORT PROPAGATION FOR THE DERRIDA-LEBOWITZ-SPEER-SPOHN EQUATION AND QUANTUM DRIFT-DIFFUSION MODELS
Get PDFAbstract. We show that weak solutions of the Derrida-Lebowitz-Speer-Spohn equation display infinite speed of support propagation. We apply our method to the case of the quantum drift-diffusion equation which augments the DLSS equation with a drift term and possibly a second-order diffusion term. The proof is accomplished using weighted entropy estimates, Hardy's inequality and a family of singular weight functions to derive a differential inequality; the differential inequality shows exponential growth of the weighted entropy, with the growth constant blowing up very fast as the singularity of the weight becomes sharper. To the best of our knowledge, this is the first example of a nonnegativity-preserving higher-order parabolic equation displaying infinite speed of support propagation
Comparative analysis of conventional and organic farming systems: Nitrogen surpluses and nitrogen losses
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Personalized Education; Solving a Group Formation and Scheduling Problem for Educational Content
Get PDFABSTRACT Wether teaching in a classroom or a Massive Online Open Course it is crucial to present the material in a way that benefits the audience as a whole. We identify two important tasks to solve towards this objective; (1.) group students so that they can maximally benefit from peer interaction and (2.) find an optimal schedule of the educational material for each group. Thus, in this paper we solve the problem of team formation and content scheduling for education. Given a time frame d, a set of students S with their required need to learn different activities T and given k as the number of desired groups, we study the problem of finding k group of students. The goal is to teach students within time frame d such that their potential for learning is maximized and find the best schedule for each group. We show this problem to be NP-hard and develop a polynomial algorithm for it. We show our algorithm to be effective both on synthetic as well as a real data set. For our experiments we use real data on students' grades in a Computer Science department. As part of our contribution we release a semi-synthetic dataset that mimics the properties of the real data
A product-mix decision model using green manufacturing technologies under activity-based costing
Get PDFTheory of constraints (TOC) Product-mix decision Mathematical programming approach a b s t r a c t The purpose of this study is to assess how the integration of activity-based costing (ABC) and the theory of constraints (TOC), as well as the application of a mixed-integer programming (MIP) model, can assist in making decisions about product-mix using green manufacturing technologies (GMTs). This study proposes a mathematical programming model to analyze the profitability of a product-mix decision based on the ABC and TOC, with the adoption of new GMTs. Using a numerical example from a metal component parts manufacturer in the automotive industry, the findings of this study provide insight into the value of mathematical programming approaches for GMTs investment and product-mix decision making based on ABC systems while simultaneously improving the value of green manufacturing technology investments
Pharmaceutical Education Assessment of predictive value of admission criteria of candidates for pharmaceutical studies -an empirical investigation
No full textABSTRACT Aim: Assessment of predictive value of results of maturity exams applied as admission criteria for pharmaceutical studies at the Medical University of Warsaw (MUW) between 2010-2012. Material and methods: Data of 390 students who began their studies and completed their first year of full-time studies at the pharmaceutical department of MUW. Admission data included: total score gained by a candidate, score concerning biology, chemistry and mathematics. Results in three subjects included in the first year studies curriculum were assessed (Anatomy, Biology with genetics and Pharmaceutical Botany) and a grade point average (GPA) covering this period of time. In order to perform predictive assessment, the analysis of correlation was applied as well as multiple regressions. Results: A model of the function of regression in form of: GPA=0.012• (total ranking points) -0.234• (gender) explains sufficiently the changeability of results obtained by students after their first year of studies (F=14.984 P<0.000001). The results of analysis point out that indeed men have lower chances of achieving a higher GPA after their first year than women (β=-0.156). Moreover, GPA value prediction after the first year of studies shows that for every additional ranking point achieved during recruitment, the increase in score is on average 0.236. Conclusion: The total of ranking points achieved by a candidate accepted to pharmaceutical studies is of significance when considering educational outcomes obtained after the first year of studies. Mastering the system of accepting candidates to university may lower the failure rate among the students of a difficult and demanding major such as pharmaceutical one
A design method for robust and quadratic optimal MIMO linear controllers
Get PDFa b s t r a c t In this paper a design method was formulated to deal with robustness and performance specifications for any MIMO linear controller. The controller tuning procedure was expressed as an optimization problem in which novel time-domain integrals of the weighted squared error and weighted squared control signals, with initial state zero and inputs not necessarily defined over the Lebesgue normed space ðL 2 þ Þ, were minimized. The control robustness is achieved by constraining the minimization such that the maximum complex/real ratio of the closed-loop control system eigenvalues was lower than one. The proposed tuning method was applied in the design of linear controllers with PID structure for a CSTR with disturbance noise and a nonlinear CSTR with control signal saturations, both reported in literature. The results show that the proposed control systems surpass the performance and robustness characteristics of the controllers designed with other reported methods