Frame Shift/warp Compensation for the ARID Robot System

The Automatic Radiator Inspection Device (ARID) is a system aimed at automating the tedious task of inspecting orbiter radiator panels. The ARID must have the ability to aim a camera accurately at the desired inspection points, which are in the order of 13,000. The ideal inspection points are known; however, the panel may be relocated due to inaccurate parking and warpage. A method of determining the mathematical description of a translated as well as a warped surface by accurate measurement of only a few points on this surface is developed here. The method uses a linear warp model whose effect is superimposed on the rigid body translation. Due to the angles involved, small angle approximations are possible, which greatly reduces the computational complexity. Given an accurate linear warp model, all the desired translation and warp parameters can be obtained by knowledge of the ideal locations of four fiducial points and the corresponding measurements of these points on the actual radiator surface. The method uses three of the fiducials to define a plane and the fourth to define the warp. Given this information, it is possible to determine a transformation that will enable the ARID system to translate any desired inspection point on the ideal surface to its corresponding value on the actual surface

Redundant drive current imbalance problem of the Automatic Radiator Inspection Device (ARID)

The Automatic Radiator Inspection Device (ARID) is a 4 Degree of Freedom (DOF) robot with redundant drive motors at each joint. The device is intended to automate the labor intensive task of space shuttle radiator inspection. For safety and redundancy, each joint is driven by two independent motor systems. Motors driving the same joint, however, draw vastly different currents. The concern was that the robot joints could be subjected to undue stress. It was the objective of this summer's project to determine the cause of this current imbalance. In addition it was to determine, in a quantitative manner, what was the cause, how serious the problem was in terms of damage or undue wear to the robot and find solutions if possible. It was concluded that most problems could be resolved with a better motor control design. This document discusses problems encountered and possible solutions

On the Development and Characterization of PMA-based SAW Sensing Devices

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A Portable System for Detecting Infrasound Using a Microcontroller

The purpose of this project was to create a device to detect infrasound communication from elephants. The device was designed and prototyped to be capable of monitoring an input signal for infrasound. If infrasound is detected, an audible alarm is sounded. This device can record audio signals for long periods of time to a digital storage device. It can be utilized for other areas of study with some modification. For example, by selecting appropriate sensors the device can be used for studying vibrations in structures. The device is low-cost so it would be able to be procured more easily and in higher quantities than more expensive and cumbersome laboratory monitoring equipment. This device could also be used as an educational and research device for students studying animal behavior in the field and laboratory. Infrasound is not limited to only elephants, but hippopotamuses, rhinoceroses and giraffes also communicate with infrasound. Environmental infrasound from sources such as wind turbines, sonic booms, explosions, tornadoes, and earthquakes can also be monitored

Multibeam bathymetry of Lipari island

Very high resolution bathymetric map obtained through multibeam echo-sounders data are crucial to generate accurate Digital Elevation Terrain Models from which the morphological setting of active volcanic areas can be analyzed in detail. Here we show and discuss the main results from the first multibeam bathymetric survey performed in shallow-waters around the Island of Lipari, the largest and the most densely populated of the Aeolian islands (Southern Italy). Data have been collected in the depth range of 0.1-150 m and complete the already existent high-resolution multibeam bathymetry realized between 100 and 1300 m water depth. The new ultra-high resolution bathymetric maps at 0.1-0.5 m provide new insights on the shallow seafloor of Lipari, allowing to detail a large spectrum of volcanic, erosive-depositional and anthropic features. Moreover, the presented data allow outlining the recent morphological evolution of the shallow coastal sector of this active volcanic island, indicating the presence of potential geo-hazard factors in shallow waters

CdO-based nanostructures as novel CO2 gas sensors

Crystalline Cd(OH)2/CdCO3 nanowires, having lengths in the range from 0.3 up to several microns and 5–30 nm in diameter, were synthesized by a microwave-assisted wet chemical route and used as a precursor to obtain CdO nanostructures after a suitable thermal treatment in air. The morphology and microstructure of the as-synthesized and annealed materials have been investigated by scanning electron microscopy, transmission electron microscopy, x-ray diffraction and thermogravimetry–differential scanning calorimetry. The change in morphology and electrical properties with temperature has revealed a wire-to-rod transformation along with a decreases of electrical resistance. Annealed samples were printed on a ceramic substrate with interdigitated contacts to fabricate resistive solid state sensors. Gas sensing properties were explored by monitoring CO2 in synthetic air in the concentration range 0.2–5 v/v% (2000–50 000 ppm). The effect of annealing temperature, working temperature and CO2 concentration on sensing properties (sensitivity, response/recovery time and stability) were investigated. The results obtained demonstrate that CdO-based thick films have good potential as novel CO2 sensors for practical applications

Prioritising systemic cancer therapies applying ESMO's tools and other resources to assist in improving cancer care globally:the Kazakh experience

BACKGROUND: In Kazakhstan, cancer is the second leading cause of death with a major public health and economic burden. In the last decade, cancer care and cancer medicine costs have significantly increased. To improve the efficiency and efficacy of cancer care expenditure and planning, the Kazakhstan Ministry of Health requested assistance from the World Health Organization (WHO) and the European Society for Medical Oncology (ESMO) to review its systemic cancer treatment protocols and essential medicines list and identify high-impact, effective regimens. MATERIALS AND METHODS: ESMO developed a four-phase approach to review Kazakhstan cancer treatment protocols: (i) perform a systematic analysis of the country’s cancer medicines and treatment protocols; (ii) cross-reference the country’s cancer protocols with the WHO Model List of Essential Medicines, the ESMO-Magnitude of Clinical Benefit Scale and the European Medicines Agency’s medicine availability and indications database; (iii) extract treatment recommendations from the ESMO Clinical Practice Guidelines; (iv) expert review for all cancer medicines not on the WHO Model List of Essential Medicines and the country treatment protocols. RESULTS: This ESMO four-phase approach led to the update of the Kazakhstan national essential cancer medicines list and the list of cancer treatment protocols. This review has led to the withdrawal of several low-value or non-evidence-based medicines and a budget increase for cancer care to include all essential and highly effective medicines and treatment options. CONCLUSION: When applied effectively, this four-phase approach can improve access to medicines, efficiency of expenditure and sustainability of cancer systems. The WHO–ESMO collaboration illustrated how, by sharing best practices, tools and resources, we can address access to cancer medicines and positively impact patient care

A Monitoring Framework with Integrated Sensing Technologies for Enhanced Food Safety and Traceability

A novel and low-cost framework for food traceability, composed by commercial and proprietary sensing devices, for the remote monitoring of air, water, soil parameters and herbicide contamination during the farming process, has been developed and verified in real crop environments. It offers an integrated approach to food traceability with embedded systems supervision, approaching the problem to testify the quality of the food product. Moreover, it fills the gap of missing low-cost systems for monitoring cropping environments and pesticides contamination, satisfying the wide interest of regulatory agencies and final customers for a sustainable farming. The novelty of the proposed monitoring framework lies in the realization and the adoption of a fully automated prototype for in situ glyphosate detection. This device consists of a custom-made and automated fluidic system which, leveraging on the Molecularly Imprinted Polymer (MIP) sensing technology, permits to detect unwanted glyphosate contamination. The custom electronic mainboard, called ElectroSense, exhibits both the potentiostatic read-out of the sensor and the fluidic control to accomplish continuous unattended measurements. The complementary monitored parameters from commercial sensing devices are: temperature, relative humidity, atmospheric pressure, volumetric water content, electrical conductivity of the soil, pH of the irrigation water, total Volatile Organic Compounds (VOCs) and equivalent CO (Formula presented.). The framework has been validated during the olive farming activity in an Italian company, proving its efficacy for food traceability. Finally, the system has been adopted in a different crop field where pesticides treatments are practiced. This has been done in order to prove its capability to perform first level detection of pesticide treatments. Good correlation results between chemical sensors signals and pesticides treatments are highlighted

Determination of the Jet Energy Scale at the Collider Detector at Fermilab

A precise determination of the energy scale of jets at the Collider Detector at Fermilab at the Tevatron $p\bar{p}$ collider is described. Jets are used in many analyses to estimate the energies of partons resulting from the underlying physics process. Several correction factors are developed to estimate the original parton energy from the observed jet energy in the calorimeter. The jet energy response is compared between data and Monte Carlo simulation for various physics processes, and systematic uncertainties on the jet energy scale are determined. For jets with transverse momenta above 50 GeV the jet energy scale is determined with a 3% systematic uncertainty

Expert system for predicting reaction conditions: The Michael reaction case

© 2015 American Chemical Society. A generic chemical transformation may often be achieved under various synthetic conditions. However, for any specific reagents, only one or a few among the reported synthetic protocols may be successful. For example, Michael β-addition reactions may proceed under different choices of solvent (e.g., hydrophobic, aprotic polar, protic) and catalyst (e.g., Brønsted acid, Lewis acid, Lewis base, etc.). Chemoinformatics methods could be efficiently used to establish a relationship between the reagent structures and the required reaction conditions, which would allow synthetic chemists to waste less time and resources in trying out various protocols in search for the appropriate one. In order to address this problem, a number of 2-classes classification models have been built on a set of 198 Michael reactions retrieved from literature. Trained models discriminate between processes that are compatible and respectively processes not feasible under a specific reaction condition option (feasible or not with a Lewis acid catalyst, feasible or not in hydrophobic solvent, etc.). Eight distinct models were built to decide the compatibility of a Michael addition process with each considered reaction condition option, while a ninth model was aimed to predict whether the assumed Michael addition is feasible at all. Different machine-learning methods (Support Vector Machine, Naive Bayes, and Random Forest) in combination with different types of descriptors (ISIDA fragments issued from Condensed Graphs of Reactions, MOLMAP, Electronic Effect Descriptors, and Chemistry Development Kit computed descriptors) have been used. Models have good predictive performance in 3-fold cross-validation done three times: balanced accuracy varies from 0.7 to 1. Developed models are available for the users at http://infochim.u-strasbg.fr/webserv/VSEngine.html. Eventually, these were challenged to predict feasibility conditions for ∼50 novel Michael reactions from the eNovalys database (originally from patent literature)