Automated extraction of disease-gene relationships from MEDLINE

The increasing amount of scientific information available to researchers in the form of biomedical literature is beginning to bring about a need for the development of tools to extract information automatically from these sources. One segment of information of particular interest to researchers is the linkage information between genes and diseases. These linkages can help researchers interpret large-scale genomics studies as well as make logical connections between gene expression levels and certain phenotypes. To make the finding and collecting of this information practical, automated methods of information extraction are required. In this paper, I propose a method for the automated extraction and database storage of linkages between genes and diseases from MEDLINE text using a combination of term co-occurrence and natural language processing techniques. This method incorporates pre-defined lexicons for genes and diseases, tokenization, statistically-driven part-of-speech tagging and chunking, as well as template matching based on a set of training templates to find relationship-containing statements in the MEDLINE text. Results of an experiment on a test set of 50 abstracts demonstrate that this method to extract disease: gene relationships from MEDLINE text can be applied with success, giving a precision of 97% and a recall between 51% and 78%

Aquatic Diptera as Indicators of Pollution in a Midwestern Stream

Author Institution: Robert A. Taft Sanitary Engineering Center, Public Health Service, Cincinnati, Ohi

Some recent results in aerospace vehicle trajectory optimization techniques

Algorithms and computation techniques for solving trajectory optimization problem

An ensemble of online estimation methods for one degree-of-freedom models of unmanned surface vehicles: applied theory and preliminary field results with eight vehicles

In this paper we report an experimental evaluation of three popular methods for online system identification of unmanned surface vehicles (USVs) which were implemented as an ensemble: certifiably stable shallow recurrent neural network (RNN), adaptive identification (AID), and recursive least squares (RLS). The algorithms were deployed on eight USVs for a total of 30 hours of online estimation. During online training the loss function for the RNN was augmented to include a cost for violating a sufficient condition for the RNN to be stable in the sense of contraction stability. Additionally we described an efficient method to calculate the equilibrium points of the RNN and classify the associated stability properties about these points. We found the AID method had lowest mean absolute error in the online prediction setting, but a weighted ensemble had lower error in offline processing.Comment: v1) 8 Pages, 5 Figures, To appear at 2023 RSJ/IEEE Conference on Intelligent Robotics and Systems (IROS) in Detroit, Michigan, USA, v2) corrected error in reference

Product development within the framework of a National Casting Technology Centre

Published ArticleThe need for a state of the art advanced National Casting Technology Centre (NCTC) has been widely supported throughout industry and recognised as an important facilitator in the growth of the foundry industry. This initiative also aligns itself with the government's Advanced Manufacturing Technology Strategy (AMTS), which is an implementation strategy in support of the South African government's Integrated Manufacturing Strategy (IMS) and National R&D Strategy (NRDS). The AMTS aims at supporting and developing the downstream high technology manufacturing industry, inter alia through the aerospace, automotive and metals sectors. In light of the above and in an effort to retain and expand the current national skills, expertise and facilities in advanced casting technologies, the National Product Development Centre at the CSIR has initiated a process of establishing a National Casting Technology Centre (NCTC). The establishment of the NCTC provides a supportive technology platform for the Advanced Metals Initiative (AMI), which was launched in 2003. The primary objective of the NCTC is to preserve and expand the national expertise and capabilities in cast metals manufacturing by supporting the local casting industry with process development, technology transfer and skills enhancement in order to increase their global competitiveness

Natural resources inventory and monitoring in Oregon with ERTS imagery

Multidiscipline team interpretation of ERTS satellite and highflight imagery is providing resource and land use information needed for land use planning in Oregon. A coordinated inventory of geology, soil-landscapes, forest and range vegetation, and land use for Crook County, illustrates the value of this approach for broad area and state planning. Other applications include mapping fault zones, inventory of forest clearcut areas, location of forest insect damage, and monitoring irrigation development. Computer classification is being developed for use in conjunction with visual interpretation

Adaptive and Collaborative Bathymetric Channel-Finding Approach for Multiple Autonomous Marine Vehicle

This paper reports an investigation into the problem of rapid identification of a channel that crosses a body of water using one or more Unmanned Surface Vehicles (USV). A new algorithm called Proposal Based Adaptive Channel Search (PBACS) is presented as a potential solution that improves upon current methods. The empirical performance of PBACS is compared to lawnmower surveying and to Markov decision process (MDP) planning with two state-of-the-art reward functions: Upper Confidence Bound (UCB) and Maximum Value Information (MVI). The performance of each method is evaluated through comparison of the time it takes to identify a continuous channel through an area, using one, two, three, or four USVs. The performance of each method is compared across ten simulated bathymetry scenarios and one field area, each with different channel layouts. The results from simulations and field trials indicate that on average multi-vehicle PBACS outperforms lawnmower, UCB, and MVI based methods, especially when at least three vehicles are used.Comment: (v1) Submitted to IEEE International Conference on Robotics and Automation (ICRA) 202

Pharmacology of DB844, an orally active aza analogue of pafuramidine, in a monkey model of second stage human African trypanosomiasis

Novel drugs to treat human African trypanosomiasis (HAT) are still urgently needed despite the recent addition of nifurtimox-eflornithine combination therapy (NECT) to WHO Model Lists of Essential Medicines against second stage HAT, where parasites have invaded the central nervous system (CNS). The pharmacology of a potential orally available lead compound, N-methoxy-6-{5-[4-(N-methoxyamidino) phenyl]-furan-2-yl}-nicotinamidine (DB844), was evaluated in a vervet monkey model of second stage HAT, following promising results in mice. DB844 was administered orally to vervet monkeys, beginning 28 days post infection (DPI) with Trypanosoma brucei rhodesiense KETRI 2537. DB844 was absorbed and converted to the active metabolite 6-[5-(4-phenylamidinophenyl)-furanyl-2-yl]-nicotinamide (DB820), exhibiting plasma C(max) values of 430 and 190 nM for DB844 and DB820, respectively, after the 14th dose at 6 mg/kg qd. A 100-fold reduction in blood trypanosome counts was observed within 24 h of the third dose and, at the end of treatment evaluation performed four days post the last drug dose, trypanosomes were not detected in the blood or cerebrospinal fluid of any monkey. However, some animals relapsed during the 300 days of post treatment monitoring, resulting in a cure rate of 3/8 (37.5%) and 3/7 (42.9%) for the 5 mg/kg×10 days and the 6 mg/kg×14 days dose regimens respectively. These DB844 efficacy data were an improvement compared with pentamidine and pafuramidine both of which were previously shown to be non-curative in this model of CNS stage HAT. These data show that synthesis of novel diamidines with improved activity against CNS-stage HAT was possible