Geared robot manipulators with a jointed unit: Kinematic analysis and its application

An efficient and systematic methodology for the kinematic analysis of geared robot manipulators (GRMs) with a jointed unit is presented. It is shown that, by decomposing mechanical transmission lines of a GRM into serially connected jointed and disjointed units, kinematic relation between local inputs and local outputs of admissible jointed units can be systematically formulated. Accordingly, angular displacements of input links with respect to their associated primary links can be symbolically expressed in terms of joint angles by a unit‐by‐unit evaluation procedure. This unit‐by‐unit evaluation procedure provides better kinematic insights into how input torques are transmitted to various joints. It is also shown that an actuator in a GRM with a jointed unit can drive nonconsecutive joints by proper design of its gear train. A 3 degrees of freedom GRM with a jointed unit is used as an illustrative example. © 2001 John Wiley & Sons, Inc.     

Results from a Forensic Investigation of a Failed Cement Treated Base

After only 2 months in service, the frontage road of US 290 developed a series of depressions that caused a very poor ride. The main cause of the premature failure was attributed to disintegration of the cement treated base (CTB) layer. This was attributed to two primary factors: (1) a very coarse gradation of the aggregate used in the CTB layer which produced a mix that was prone to segregation during placement; and (2) the CTB layer was placed in two lifts, which were not well bonded together. Another contributing factor was the lack of bond between the CTB and the hot mix asphalt (HMA) surface layer. Secondary factors include high air voids in the HMA layer and low HMA layer thickness. The material, when prepared carefully in the lab at the design cement content, passed the strength requirement of 2.07?MPa. But this coarse mix appears to have been difficult to place correctly in the field. The coarsely graded aggregate used on this project appears to be prone to segregation, either during placement or compaction. The ground penetration radar results (with confirmation by core samples) indicated that most of the problems were at the bottom of the upper CTB lift. The CTB was placed in two lifts and very poor condition was found between the two CTB layers. This problem was coupled with a thin, porous, and poorly bonded HMA layer that permitted moisture to enter the CTB layer. Similar failures have also been reported recently on other CTB projects in Houston.     

Power plant based on a variable-speed diesel generator

The paper shows the energetic and economic expediency of using a variable-speed diesel power plant. Functional and structural schemes of the variable-speed diesel power plant are described.     

Expression of a Deschampsia antarctica Desv. Polypeptide with Lipase Activity in a Pichia pastoris Vector

The current study isolated and characterized the Lip3F9 polypeptide sequence of Deschampsia antarctica Desv. (GeneBank Accession Number {"type":"entrez-nucleotide","attrs":{"text":"JX846628","term_id":"443427649","term_text":"JX846628"}}JX846628), which was found to be comprised of 291 base pairs and was, moreover, expressed in Pichia pastoris X-33 cells. The enzyme was secreted after 24 h of P. pastoris culture incubation and through induction with methanol. The expressed protein showed maximum lipase activity (35 U/L) with an optimal temperature of 37 °C. The lipase-expressed enzyme lost 50% of its specific activity at 25 °C, a behavior characteristic of a psychrotolerant enzyme. Recombinant enzyme activity was measured in the presence of ionic and non-ionic detergents, and a decrease in enzyme activity was detected for all concentrations of ionic and non-ionic detergents assessed.     

Effects of cobalt and cobalt oxide buffer layers on nucleation and growth of hot filament chemical vapor deposition diamond films on silicon (100)

An initial study on the nucleation and growth of diamond, using hot filament chemical vapor deposition (HFCVD) technique, was carried out on Co and CoO thin buffer layers on non-carbon substrates (Si (100)), and the results were compared with conventional scratching method. The substrate temperature during the growth was maintained at 750±50 °C. A mixture of CH₄ and H₂ (1: 100 volume %) was used for deposition. The total pressure during the two hour deposition was 30±2 Torr. X-ray photoelectron spectroscopy (XPS) study showed the diamond nucleation at different time periods on the Co and CoO seed layers. It is observed that Co helps in nucleation of diamond even though it is known to degrade the quality of diamond film on W-C substrate. The reason for improvement in our study is attributed to (i) the low content of Co (~0.01%) compared to W-C substrate (~5–6%), (ii) formation of CoSi₂ phase at elevated temperature, which might work as nucleation sites for diamond. SEM analysis reveals a change in the morphology of diamond film grown on cobalt oxide and a significant reduction in the size of densely packed crystallites. Raman spectroscopic analysis further suggests an improvement in the quality of the film grown on CoO buffer layer.     

La(0.7)Sr(0.3)MnO3 nanoparticles based ultra-high sensitive ammonia chemical sensor

A facile, reliable, reproducible and ultra-high sensitive aqueous ammonia chemical sensor has been fabricated based on the utilization of La(0.7)Sr(0.3)MnO3 nanoparticles (LSMO NPs), as efficient electron mediators, and reported in this paper. The LSMO NPs were prepared by hydrothermal protocol followed by the annealing process and characterized in detail in terms of their mophological, structural and compositional properties. The I-V technique based aqueous ammonia sensor exhibits an ultra-high sensitivity of 494.68 +/- 0.01 microA cm(-2)mM(-1) and very low-detection limit of 0.2 microM with a response time less than 10 s. To the best of our knowledge, this is the first report in which LSMO is used as an efficient electron mediator for the fabrication of aqueous ammonia chemical sensor. Moreover, by comparing the literature, it is confirmed that the fabricated sensor exhibits highest sensitivity towards the detection of aqueous ammonia. This LSMO nanomaterial based research broadens the range of efficient electron mediators utilized for the fabrication of ultra-high sensitive chemical sensors.     

A reusable structural design for mobile collaborative applications

Architecting mobile collaborative applications has always been a challenge for designers. However, counting on a structural design as a reference can help developers to reduce risks and efforts involved in system design. This article presents a reusable architecture which helps modeling the communication and coordination services required by mobile collaborative applications to support collaboration among users. This architecture has been used as a basis for the design of several mobile systems. Two of them are presented in this article to show the applicability of the proposal to real world collaborative systems.     

A survey of artificial neural network training tools

Artificial neural networks (ANN) are currently an additional tool which the engineer can use for a variety of purposes. Classification and regression are the most common tasks; however, control, modeling, prediction and forecasting are common tasks as well. For over three decades, the field of ANN has been the center of intense research. As a result, one of the outcomes has been the development of a large set of software tools used to train these kinds of networks, making the selection of an adequate tool difficult for a new user. This paper aims to help the ANN user choose the most appropriate tool for its application by providing a large survey of the solutions available, as well as listing and explaining their characteristics and terms of use. The paper limits itself to focusing on the tools which were developed for ANN and the relevant characteristics of these tools, such as the operating systems, hardware requirements, license types, architectures and algorithms available.     

The craving to smoke in flight attendants: Relations with smoking deprivation, anticipation of smoking, and actual smoking.

In the study, the authors examined the effects of smoking deprivation, anticipation of smoking, and actual smoking on the craving to smoke. Flight attendants who were light to heavy smokers rated their craving to smoke at predetermined time points during a 2-way short flight (each leg 3–5.5 hr) and a 1-way long flight (8–13 hr). In both short and long flights, craving increased gradually and peaked as landing approached. Craving levels at the end of the 1st leg of the short flights were equal to those at the end of the long flight and were much higher than those at the parallel time point in the long flight. In the short flight, craving levels at the beginning of the 2nd leg dropped relative to the end of the 1st leg, both for participants who smoked during the intermission and for those who did not, though the drop was steeper for the former. The results provide additional evidence for the role of psychological factors in determining the craving to smoke in a naturalistic setting. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Enhancing breast pectoral muscle segmentation performance by using skip connections in fully convolutional network

The precise detection and segmentation of pectoral muscle areas in mediolateral oblique (MLO) views is an essential step in the development of a computer-aided diagnosis system to access breast malignant lesions or parenchyma. The goal of this article is to develop a robust and fully automatic algorithm for pectoral muscle segmentation from mammography images. This paper presents an image enhancement approach that improves the quality of mammogram scans and a convolutional neural network-based fully convolutional network architecture enhanced with residual connections for automatic segmentation of the pectoral muscle from the MLO views of a digital mammogram. For this purpose, the model is tested and trained on three different mammogram datasets named MIAS, INBREAST, and DDSM. The ground truth labels of the pectoral muscle were identified under the supervision of experienced radiologists. For training and testing, 10-fold cross-validation was used. The proposed model was compared with baseline U-Net-based architecture. Finally, we used a postprocessing step to find the actual boundary of the pectoral muscle. Our presented architecture generated a mean Intersection over Union (IoU) of 97%, dice similarity coefficient (DSC) of 96% and 98% accuracy on testing data. The proposed architecture for pectoral muscle segmentation from the MLO views of mammogram images with high accuracy and dice score can be quickly merged with the breast tumor segmentation problem.