Some rheological properties of new and used mineral lubricant and biolubricant for tractors

ArticleIt is important to know physical characteristics of lubricating oils to ensure the highest reliability for operation of device. The use of ecological lubricants depends on their characteristics; the most important are density and viscosity, protection against wear and tear, corrosion resistance etc. The objective of this work was to find changes of the rheological properties of the synthetic oil and bio lubricant. We compared two different oils in our measurements. One sample was synthetic oil and the other was mineral oil (bio lubricant). Both oils are universal oils for tractors. Further, comparison of new and used sample after million cycles was performed. The density and the dynamic viscosity show strong exponentially decreasing dependence. With the increasing temperature, values of the both properties, decreased. It can be also observed that used samples have lower viscosity and density. The results presented in this article can be important when putting ecological lubricants into operation

Phase formation of a biocompatible Ti-based alloy under kinetic constraints studied via in-situ high-energy X-ray diffraction

The biocompatible Ti40Cu34Pd14Zr10Sn2 bulk metallic glass was rapidly heated, also known as flash-annealed, at varying heating rates up to 1579 K/s. Thereby, the phase formation was characterized via advanced in-situ high-energy X-ray diffraction. It has been found that the evolving kinetic constraints can be used as a tool to deliberately alter the crystalline phase formation. This novel processing route permits to select phases to crystallize to a predefined fraction and, thus, to potentially design the microstructure of materials according to a specified property-profile. Consequently, flash-annealing poses a unique synthesis route to design materials with, for instance, good biomechanical compatibility

Mechanical performance and corrosion behaviour of Zr-based bulk metallic glass produced by selective laser melting

Nearly fully dense, glassy Zr52.5Cu17.9Ni14.6Al10Ti5 bulk specimens were fabricated by selective laser melting (SLM) and their behaviour during compressive loading, during wear testing and in a corrosive medium was investigated. Their performance was compared with as-cast material of the same composition. The additively manufactured samples exhibit a yield strength around 1700 MPa combined with a plastic strain of about 0.5% after yielding despite the residual porosity of 1.3%, which is distributed uniformly in the samples. The propagation of shear bands in the bulk metallic glass prepared by SLM was studied. The specific wear rate and the worn surfaces demonstrated that similar wear mechanisms are active in the SLM and the as-cast samples. Hence, manufacturing the glass in layers does not adversely affect the wear properties. The same holds for the corrosion tests, which were carried out in 0.01 M Na2SO4 and 0.1 M NaCl electrolyte. The anodic polarization curves of SLM samples and as-cast samples revealed a similar corrosion behaviour. However, the SLM samples have a slightly reduced susceptibility to pitting corrosion and exhibit an improved surface healing ability, which might be attributed to an improved homogeneity of the additively manufactured glass

Wind Field of a Nonmesocyclone Anticyclonic Tornado Crossing the Hong Kong International Airport

A nonmesocyclone tornado traversed the Hong Kong International Airport on September 6, 2004 directly impacting a surface weather station. This allowed for 1-second 10-meter above ground level (AGL) wind observations through the core of the tornado. Integration of these 10-meter AGL wind data with Ground-Based Velocity Track (GBVTD) wind retrievals derived from LIDAR data provided a time history of the three-dimensional wind field of the tornado. These data indicate a progressive decrease in radial inflow with time and little to no radial inflow near the time the tornado crosses the surface weather station. Anemometer observations suggest that the tangential winds approximate a modified-Rankine vortex outside the radius of maximum winds, suggesting that frictionally induced radial inflow was confined below 10 m AGL. The radial-height distribution of angular momentum depicts an increase in low-level angular momentum just prior to the tornado reaching its maximum intensity

Observational and Modeling Analysis of Land–Atmopshere Coupling over Adjacent Irrigated and Rainfed Cropland during the GRAINEX Field Campaign

The Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 to investigate Land-Atmosphere (L-A) coupling just prior to and through the growing season across adjacent, but distinctly unique, soil moisture regimes (contrasting irrigated and rainfed fields). GRAINEX was uniquely designed for the development and analysis of an extensive observational dataset for comprehensive process studies of L-A coupling, by focusing on irrigated and rainfed croplands in a ~100 x 100 km domain in southeastern Nebraska. Observation platforms included multiple NCAR EOL Integrated Surface Flux Systems and Integrated Sounding Systems, NCAR CSWR Doppler Radar on Wheels, 1200 radiosonde balloon launches from 5 sites, the NASA GREX airborne L-Band radiometer, and 75 University of Alabama-Huntsville Environmental Monitoring Economic Monitoring Sensor Hubs (EMESH mesonet stations). An integrated observational and modeling approach to advance knowledge of L-A coupling processes and precipitation impacts in regions of heterogeneous soil moisture will be presented. Specifically, through observation of land surface states, surface fluxes, near surface meteorology, and properties of the atmospheric column, an examination of the diurnal planetary boundary layer evolving characteristics will be presented. Results from a hierarchy of modeling platforms (e.g. single column, large-eddy, and mesoscale simulations) will also be presented to complement the observational findings. The modeling effort will generate high spatiotemporal resolution datasets to: 1) generate a multi-physics ensemble to test the robustness and potentially advance physical parameterizations in high resolution weather and climate models, 2) comparison of prescribed forcing from observations and those from offline land surface model simulations and high resolution operational analyses, 3) determine the ability of model simulations to reproduce observed boundary layer evolution, with particular attention to the processes that compose the L-A coupling chain and metrics (e.g. mixing ratio diagrams), and 4) in combination with observations, isolate the impacts of soil moisture heterogeneity on planetary boundary layer characteristics, cloud development, precipitation, mesoscale circulation patters and boundary layer development. Initial results from the observational and modeling analysis will be presented

A Novel Hybrid Scheme Using Genetic Algorithms and Deep Learning for the Reconstruction of Portuguese Tile Panels

This paper presents a novel scheme, based on a unique combination of genetic algorithms (GAs) and deep learning (DL), for the automatic reconstruction of Portuguese tile panels, a challenging real-world variant of the jigsaw puzzle problem (JPP) with important national heritage implications. Specifically, we introduce an enhanced GA-based puzzle solver, whose integration with a novel DL-based compatibility measure (DLCM) yields state-of-the-art performance, regarding the above application. Current compatibility measures consider typically (the chromatic information of) edge pixels (between adjacent tiles), and help achieve high accuracy for the synthetic JPP variant. However, such measures exhibit rather poor performance when applied to the Portuguese tile panels, which are susceptible to various real-world effects, e.g., monochromatic panels, non-squared tiles, edge degradation, etc. To overcome such difficulties, we have developed a novel DLCM to extract high-level texture/color statistics from the entire tile information. Integrating this measure with our enhanced GA-based puzzle solver, we have demonstrated, for the first time, how to deal most effectively with large-scale real-world problems, such as the Portuguese tile problem. Specifically, we have achieved 82% accuracy for the reconstruction of Portuguese tile panels with unknown piece rotation and puzzle dimension (compared to merely 3.5% average accuracy achieved by the best method known for solving this problem variant). The proposed method outperforms even human experts in several cases, correcting their mistakes in the manual tile assembly

Effects of spoilage on nitrogen and carbon stable isotopes signatures of the clam Ruditapes decussatus

Fish and seafood products are highly susceptible to post-mortem spoilage due to autolytic reactions at start, then microbiological activity and eventually oxidative reactions. Chemical and microbiological parameters are usually used to assess quality and make decisions for protecting public health, but they lack precision in defining which spoilage pathway is occurring at each moment. The objective of this work was to assess the effects of spoilage reactions on nitrogen and carbon stable isotopes in the grooved carpet shell clam, Ruditapes decussatus, and compare them to biochemical indicators of seafood deterioration, in order to better understand the relations between the different spoilage pathways during commercial storage conditions. Clams were kept in a refrigerator at 5 ºC, to simulate normal commercial storage conditions, and sampled in the beginning of the experiment, and after eight, ten and twelve days. Moisture, condition index, percentage edibility, total volatile basic nitrogen (TVB-N), pH, nitrogen and carbon percentages and stable isotopes were determined for each sampling moment. Stable isotope analyses were performed using a Costech Elemental Analyzer (ECS 4010) coupled to a ThermoFinnigan Delta V Advantage. Stable isotopes analysis, especially for nitrogen, proved to be a good tool for the study of clam deterioration. Nitrogen stable isotopes results showed a relation with other spoilage indicators, such as pH and TVB-N, and allowed identifying spoilage specific pathways, such as amino acids decarboxylation and production of volatile nitrogen compounds.info:eu-repo/semantics/publishedVersio

The 2015 Plains Elevated Convection at Night Field Project

The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night. To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings

Materiality, health informatics and the limits of knowledge production

© IFIP International Federation for Information Processing 2014 Contemporary societies increasingly rely on complex and sophisticated information systems for a wide variety of tasks and, ultimately, knowledge about the world in which we live. Those systems are central to the kinds of problems our systems and sub-systems face such as health and medical diagnosis, treatment and care. While health information systems represent a continuously expanding field of knowledge production, we suggest that they carry forward significant limitations, particularly in their claims to represent human beings as living creatures and in their capacity to critically reflect on the social, cultural and political origins of many forms of data ‘representation’. In this paper we take these ideas and explore them in relation to the way we see healthcare information systems currently functioning. We offer some examples from our own experience in healthcare settings to illustrate how unexamined ideas about individuals, groups and social categories of people continue to influence health information systems and practices as well as their resulting knowledge production. We suggest some ideas for better understanding how and why this still happens and look to a future where the reflexivity of healthcare administration, the healthcare professions and the information sciences might better engage with these issues. There is no denying the role of health informatics in contemporary healthcare systems but their capacity to represent people in those datascapes has a long way to go if the categories they use to describe and analyse human beings are to produce meaningful knowledge about the social world and not simply to replicate past ideologies of those same categories