Predicting effect of physical factors on tibial motion using artificial neural networks

The aim of this study was to predict the effect of physical factors on tibial motion by making use of artificial neural networks (ANNs). Since assessment of the tibial motion by the conventional approaches is generally difficult, this study aimed at the prediction of the relations between several physical factors (gender, age, body mass, and height) and tibial motion in terms of the ANNs. Data collected for 484 healthy subjects have been analyzed by using the ANNs. The study has given encouraging results for such a purpose. This investigation has been made to predict the rotations; especially the RTER prediction is highly satisfactory and the ANNs have been found to be very promising processing systems for modelling in the tibial rotation data assessments.     

The effect of external pressure on skin temperature distribution by thermography

1) Serial thermograms were taken after the application of various intensities and durations of localized pressure on the medial surface of the human forearm. 2) Thermal response of the body surface to localized pressure was quantified. 3) It was found that usually a time period of between 1 to 3 minutes elapsed before the body surface attained a maximum elevation of temperature from the time the localized pressure is removed. 4) It was found that increased intensity of pressure (5 psi vs. 3 psi) and longer duration (20 minutes vs. 10 minutes) caused larger thermal responses. 5) It is suggested that high resolution medical thermography may eventually become a useful tool in the fitting of prosthetic and orthotic devices and for the prediction of pressure sores formation so prophylactic measures can be started immediately on immobilized patients.     

Nanosilicon in water as a source of hydrogen: size and pH matter

We report on the interaction of silicon nanocrystals with water/alcohol solutions which results in their complete oxidation, the hydrolysis of water and hydrogen generation in amounts close to the ideal scenario. Water acts as an oxidizer while alcohol is required for efficient wetting of nanosilicon. This process results in the formation of silicon-based alcogel which can be further transferred to aerogel.     

Effect of CeO2 addition on densification and microstructure of Al2O3-YSZ composites

Alumina (Al₂O₃) and alumina-yttria stabilized zirconia (YSZ) composites containing 3 and 5 mass% ceria (CeO₂) were prepared by spark plasma sintering (SPS) at temperatures of 1350-1400 °C for 300 s under a pressure of 40 MPa. Densification, microstructure and mechanical properties of the Al₂O₃ based composites were investigated. Fully dense composites with a relative density of approximately 99% were obtained. The grain growth of alumina was inhibited significantly by the addition of 10 vol% zirconia, and formation of elongated CeAl₁₁O₁₈ grains was observed in the ceria containing composites sintered at 1400 °C. Al₂O₃-YSZ composites without CeO₂ had higher hardness than monolithic Al₂O₃ sintered body and the hardness of Al₂O₃-YSZ composites decreased from 20.3 GPa to 18.5 GPa when the content of ZrO₂ increased from 10 to 30 vol%. The fracture toughness of Al₂O₃ increased from 2.8 MPa m^1/2 to 5.6 MPa m^1/2 with the addition of 10 vol% YSZ, and further addition resulted in higher fracture toughness values. The highest value of fracture toughness, 6.2 MPa m^1/2, was achieved with the addition of 30 vol% YSZ.     

Prevention of nonmelanoma skin cancer. Standard and investigative approaches

Today, in many fields of medicine, the focus is on prevention. This discussion highlights the salient features of sunscreens, protective clothing, and education, as they relate to the hazards and potential sequelae of sun exposure and tanning parlors. It also includes information on the status of clinical and laboratory investigation in the development of agents to prevent skin cancer in high-risk individuals.     

Production and characterization of ZrO<Subscript>2</Subscript> ceramics and composites to be used for hip prosthesis

Tetragonal ZrO₂ polycrystalline (TZP) ceramics with varying yttria and ceria content (2–3 mol%) and distribution (coated or co-precipitated), and varying second phase content Al₂O₃ were prepared and investigated by means of microstructural analysis, mechanical properties, and hydrothermal stability, and ZrO₂-based composites with 35–60 vol% of electrical conductive TiN particles were developed. The effects of stabilizer content and means of addition, powder preparation, sintering conditions, and grain size have been systematically investigated. Fully dense Y-TZP ceramics, stabilized with 2–3 mol% Y₂O₃, 2 wt% Al₂O₃ can be achieved by hot pressing at 1,450 °C for 1 h. The hydrothermal stability increased with increasing overall yttria content. The jet-milled TiN powder was used to investigate the ZrO₂–TiN composites as function of the TiN content. The experimental work revealed that fully dense ZrO₂–TiN composites, stabilized with 1.75 mol% Y₂O₃, 0.75 wt% Al₂O₃, and a jet-milled TiN content ranging from 35 to 60 vol% could be achieved by hot pressing at 1,550 °C for 1 h. Transformation toughening was found as the primary toughening mechanism. The decreasing hardness and strength could be attributed to an increasing TiN grain size with increasing TiN content, whereas the decreasing toughness might be due to the decreasing contribution of transformation toughening from the tetragonal to monoclinic ZrO₂ phase transformation. The E modulus increases linearly with increasing TiN content, whereas the hydrothermal stability increases with addition of TiN content.     

Biosynthesis of (3<Emphasis Type="Italic">Z</Emphasis>,6<Emphasis Type="Italic">Z</Emphasis>,9<Emphasis Type="Italic">Z</Emphasis>)-3,6,9-Octadecatriene: The Main Component of the Pheromone Blend of <Emphasis Type="Italic">Erannis bajaria</Emphasis>

The hydrocarbons (3Z,6Z,9Z)-3,6,9-octadecatriene (3Z,6Z,9Z-18:H) and (3Z,6Z,9Z)-3,6,9-nonadecatriene (3Z,6Z,9Z-19:H) constitute the pheromone of the winter moth, Erannis bajaria. These compounds belong to a large group of lepidopteran pheromones which consist of unsaturated hydrocarbons and their corresponding oxygenated derivatives. The biosynthesis of such hydrocarbons with an odd number of carbons in the chain is well understood. In contrast, knowledge about the biosynthesis of even numbered derivatives is lacking. We investigated the biosynthesis of 3Z,6Z,9Z-18:H by applying deuterium-labeled precursors to females of E. bajaria followed by gas chromatography–mass spectrometry analysis of extracts of the pheromone gland. A mixture of deuterium-labeled [17,17,18,18-²H₄]-3Z,6Z,9Z-18:H and the unlabeled 3Z,6Z,9Z-18:H was obtained after topical application and injection of (10Z,13Z,16Z)-[2,2,3,3-²H₄]-10,13,16-nonadecatrienoic acid ([2,2,3,3-²H₄]-10Z,13Z,16Z-19:acid) or (11Z,14Z,17Z)-[3,3,4,4-²H₄]-11,14,17-icosatrienoic acid ([3,3,4,4-²H₄]-11Z,14Z,17Z-20:acid). These results are consistent with a biosynthetic pathway that starts with α-linolenic acid (9Z,12Z,15Z-18:acid). Chain elongation leads to 11Z,14Z,17Z-20:acid, which is shortened by α-oxidation as the key step to yield 10Z,13Z,16Z-19:acid. This acid can be finally reduced to an aldehyde and decarbonylated or decarboxylated to furnish the pheromone component 3Z,6Z,9Z-18:H. A similar transformation of 11Z,14Z,17Z-20:acid yields the second pheromone component, 3Z,6Z,9Z-19:H.     

Scheduling in robotic cells: process flexibility and cell layout

The focus of this study is the identical parts robotic cell scheduling problem with m machines under the assumption of process and operational flexibility. A direct consequence of this assumption is a new robot move cycle that has been overlooked in the existing literature. We prove that this new cycle dominates all classical robot move cycles considered in the literature for m?=?2. We also prove that changing the layout from an in-line robotic cell to a robot-centered cell reduces the cycle time of the proposed cycle even further, whereas the cycle times of all other cycles remain the same. For the m-machine case, we find the regions where the proposed cycle dominates the classical robot move cycles, and for the remaining regions present its worst case performance with respect to classical robot move cycles. Considering the number of machines as a decision variable, we also find the optimal number of machines that minimizes the cycle time of the proposed cycle.