Miracle-dz/UniFAR-FTUs huggingface dataset:
Engine Bearing Materials

By Dr. Dmitri Kopeliovich The durable operation of an engine bearing is achieved if its materials combine high strength (load capacity, wear resistance, cavitation resistance) with softness (compatibility, conformability, embedability.) So the bearing materials should be both strong and soft. It sounds paradoxical but all existing bearing materials are designed to combine those contradictory properties with a certain compromise. In order to achieve such compromise bearing materials have a composite structure (Fig. 1) The structure may be either layered with a soft overlay applied over a strong lining or particulate, in which small particles of a soft material are distributed in a relatively strong matrix. Some bearings combine layered and particulate composite structures.
Re-gripping analysis based on implementation of slip-detection device for robotic hand model

To develop an intelligent robotic hand, diverse approaches have been applied, including optimum gripping force and slippage analysis. In this study, a robotic hand was modeled with tactile pressure sensors. The slip detection sensor, which is represented as a rotary encoder device, was employed to indicate the slip situation features, distance and velocity. Empirical findings imply that the correlation between the distance that an object has slipped and the required re-gripping force was developed to be availed as an automatic feedback algorithm. The slippage events were revealed and analyzed to perform the control system mechanism of the re-gripping mission.
Use of dual-energy x-ray absorptiometry in non-ruminant nutrition research

ABSTRACT Precise body composition measurements are essential in animal nutrition studies because the impact of treatments is evaluated based on changes in body weight and composition. Various indirect techniques for animal compositional evaluation have been developed and evaluated for applicability in animal nutrition studies. A fast, accurate, minimally invasive method that requires little input is considered the ideal for providing information about the animal. Measurements obtained by dual-energy x-ray absorptiometry (DXA) are highly correlated with those obtained by chemical analysis [. ]
Real-Time Photorealistic 3D Map Building using Mobile Multiple Stereo Cameras Setup

This work proposes a multiple stereo cameras setup as sensing device for real time photorealistic 3D map building task. Applications include 3D photorealistic capturing of historic sites, remote exploration and navigation for autonomous robots, 3DTV, entertainment industry and much more. Particular emphasis is placed on the novel multiple cameras arrangement that minimizes the weak points found on single stereo camera system and gives advantages toward the applications that require high accuracy 3D spatial and 3D geometry information, e.g. 3D mapping, 3D positioning and trajectory estimation. A hardware prototype was constructed and it shows promising performance toward real time photorealistic 3D map building task.
Design Considerations of Power Management Control Strategies for Micro-grid Systems

The paper outlines the design considerations for electrical microgrid Power Management Model (PMM). Design considerations for decentralized power management control for a microgrid that operates in an isolated mode disconnected from the main power grid is the main focus. An example based in part on a hypothetical scenario of the transformation process of the No Name Key Island, an island in the lower Florida Keys, into a microgrid community serves as a typical scenario to formulate the analysis of optimal power flows and as a consequence the economical dispatch for photovoltaic arrays and diesel generators to meet local power demands. Three stage optimal power flow optimization problem is presented bidding, unit commitment and real time adjustment of optimal power flow for the microgrid. The optimization utilizes simplified models allowing each optimization to be done using linear programming implemented in Matlab.
Atomistic study of nanotwins in NiTi shape memory alloys

Atomistic simulations are performed to study the structure and geometrical limit of nanoscale twins in NiTi shape memory alloys. We analyze compound twins as narrow as ∼1 nm, involving a few atomic layers. A novel nanotwinned structure is found, forming through the martensitic transformation of sublattices. We predict the temperatures of phase transformation, which are consistent with experimental measurements. The results provide an atomistic basis for further study of nanometer length scale effects on the martensitic phase transformation and shape memory behavior.
Holistic Video Stitching for Street Panorama

In this paper, we address how to automatically generate a panorama for a street view from a long video sequence. We model the panorama as a low-rank matrix and formulate the problem as one of ro­ bust recovery of the low-rank matrix from highly incomplete, corrupted, deformed measurements (the video frames). We leverage powerful high­ dimensional convex optimization tools from compressive sensing of sparse signals and low-rank matrices to solve this problem. In particular, we show how the new method can effectively remove severe occlusions or corruptions (caused by trees, cars, or reflections etc.), and obtain clean intrinsic street panoramas that are consistent with all frames. We also show how our method can automatically and robustly establish pixelwise accurate registration among all the video frames. We demonstrate the effectiveness of our method by conducting extensive experimental comparison with other popular video stitching methods such as AutoStitch and Adobe Photoshop.
Wavefront Sensing Based on Partially Occluded and Extended Scene Target

In order to overcome the shortcomings of traditional wavefront achieving techniques, which cannot capture the wavefront in the case that an obstacle presents in front of the reference source, we propose and demonstrate a new wavefront measuring method by exploiting a plenoptic configuration. By processing the 4-D light-field information captured by plenoptic configuration, the obstacle's information can be distinguished and eliminated, and the preserved scene target's information can be utilized to extract the wavefront information. The numerical simulation using partially occluded and extended scene targets show that this technology is feasible, even in the situation of strong wavefront aberrations. The technology proposed in this paper can have wide applications in astronomical imaging and surveillance systems.
An optimized approach for home appliances scheduling in smart grid

In this paper, we present a novel home energy management model with enhanced load categorization and multiple scheduling options. Concepts of partial baseline and reserved interrupting loads are used to enhance the traditional load categorization. The proposed model uses multiple pricing schemes namely Time of Use (ToU) and Real Time Pricing (RTP) day ahead case. The energy cost minimization problem has been solved by multiple optimization techniques namely Knapsack and Particle Swarm Optimization (PSO). Comparative results of multiple pricing schemes have been discussed which prove the effectiveness of the proposed model.
A study of frequency radiation of human torso for gender classification

Studies on human body have shown that they radiate frequencies into space. Radiation of the human body has become attractive biometric feature that is based on holistic body information. This study presents a new technique for classification that is used to classify gender of males and females through frequency radiation analysis in torso region. The classification algorithm of k-nearest neighbor is employed for classification purposes. It was found that the proposed technique can classify gender correctly with sensitivity of 96% and specificity 73%, across 33 subjects. Experimental results proposed that the technique is suitable and can be used to classify gender using frequency radiation analysis of human torso.
Sequential Patterns for Extracting Protein-Protein Interactions from Biomedical Texts

This research report explores the use of sequential patterns in the task of proteinprotein interaction extraction from biomedical texts. We introduce two concepts of automated sequential pattern construction and validation: frequent patterns tuning (FPT) and maximal generic patterns instantiation (MGPI). In FPT, frequent patterns are first mined from the training data, and next, after filtering out irrelevant patterns, additional patterns are derived from the mined patterns using taxonomies and linguistically sound distance constraints to improve the generalizing power and to better fit the underlying structure. The MGPI, on contrary, provides more control over the pattern structure: the pattern is structurally determined by a predefined generative grammar and only specific subsequences, common to many other related generic patterns, are extracted from the training data (and subsequently validated) independently of the current generic pattern. Moreover, addressing the essentially non-sequential character of natural language, we propose a method of text preprocessing aimed to improve the performance of arbitrary interaction extraction methods employing sequential patterns. To evaluate and compare the predictive power of both sequential pattern concepts and to determine the relevancy of the preprocessing step, we present a comprehensive set of experiments performed on standard data sets annotated for protein-protein interactions. The results rise the need for discussion about suitable testing method, mostly targeting inconsistencies in interaction annotations among and within the testing corpora.
Intensity Augmented ICP for Registration of Laser Scanner Point Clouds

While using Laser Scanner for map-making or developing 3D models of objects, it is important to scan the site or the object of interest from multiple viewpoints. These different scans are then integrated to generate a complete point cloud which is then used for developing the map or 3D model of the site. ICP (Iterative Closest Point) is a standard algorithm for registration of point clouds. However, in the absence of marked 3D features which are geometrically distinct in the points clouds, that are being combined, this method tend to fail sometime. This paper exploits the radiometric data that are always obtained along with the coordinates of point cloud and devises a novel approach for scan registration. Before using radiometric data in registration process these are normalized. The algorithm presented in this paper works in two stageswith Intensity Augmented ICP (IAICP) for coarse registration stage and conventional geometric ICP at the fine registration stage. The proposed approach is successfully applied to a test data resulting in an accurate estimation of the transformation parameters. A comparison of the conventional and intensity augmented registration approaches is also presented. The results indicate the supremacy of IAICP over the ICP, as the latter is found to fail in geometrically confusing cases while intensity augmented ICP works in these cases.
Enhancing adaptive huffman coding through word by word compression for textual data

Nowadays, the volume of information that is being processed is increasing exponentially. And hence, the significance of data compression algorithms is also increasing. Data compression algorithms aim at reducing the size of data at the cost of increased computational efforts. In this paper, we propose an enhanced version of adaptive Huffman encoding technique for improving the efficiency of text file compression. In the proposed encoding technique, we devise a mechanism for compressing the text files word by word rather than the existing byte by byte compression technique. The proposed method is implemented and the results showed better performance in terms of compression ratio as well as execution time.
Design of 3.3 kW wireless battery charger for electric vehicle application considering bifurcation

Bifurcation in a resonant inductive power transfer (RIPT) system causes hard switching of the primary side inverter, decrease in efficiency and loss of control stability. Bifurcation can be avoided by either selecting complicated control strategies or by calculating the parameters of RIPT system in such a way that the system has only one resonant frequency for the entire expected range of load and coupling variations. Many control methods to tackle the bifurcation issue have been covered in the literature. This paper aims at handling the bifurcation by proposing an analytical design procedure. A fabricated system, based on the parameters calculated using presented design steps, avoids the bifurcation phenomenon for the entire coupling and load variations. A 3.3 kW wireless charger setup using series-series compensated RIPT (SS-RIPT) system and 2-phase interleaved boost power factor correction (PFC) as a front end converter has been designed using the proposed method as an example. Simulation results using MATLAB are presented to verify the proposed design methodology.
Why Hospitals Don't Learn from Failures: Organizational and Psychological Dynamics That Inhibit System Change

The importance of hospitals learning from their failures hardly needs to be stated. Not only are matters of life and death at stake on a daily basis, but also an increasing number of U.S. hospitals are operating in the red. This article reports on in-depth qualitative field research of nurses' responses to process failures in nine hospitals. It identifies two types of process failures—errors and problems—and discusses implications of each for process improvement. A dynamic model of the system in which front-line workers operate reveals an illusory equilibrium in which small process failures actually erode organizational effectiveness rather than driving learning and change in hospitals. Three managerial levers for change are identified, suggesting a new strategy for improving hospitals' and other service organizations' ability to learn from failure.
Design of an industrial human-robot system through participative simulations — Tank cleaning case study

Industrials are starting to deploy interactive robots as new solutions to improve workstations. In particular, workstations where human operators may get injured because of repetitive tasks, bad postures or heavy loads are targeted. The introduction of such interactive systems on industrial workstations brings new challenges concerning human cognitive and physical considerations to factories. We followed an approach involving operators, and ergonomics and cognitive engineering skills to improve the introduction of interactive robots in the industry. In this paper, we present the first application of our work on a pyrotechnic tank cleaning workstation. Our approach is illustrated with the design of a solution through several simulation steps involving the workstation's operators. Finally, the design of a prototype based on a teleoperated robot is introduced.
Estimation of evapotranspiration using diurnal groundwater level fluctuations: Comparison of different approaches with groundwater lysimeter data

In wetlands or riparian areas, water withdrawal by plants with access to groundwater or the capillary fringe often causes diurnal groundwater fluctuations. Various approaches use the characteristics of these fluctuations for estimation of daily groundwater evapotranspiration rates. The objective of this paper was to review the available methods, compare them with measured evapotranspiration and assess their recharge assumptions. For this purpose, we employed data of 85 rain‐free days of a weighable groundwater lysimeter situated at a grassland site in the Spreewald wetland in north‐east Germany. Measurements of hourly recharge and daily evapotranspiration rates were used to assess the different approaches. Our results showed that a maximum of 50% of the day to day variance of the daily evapotranspiration rates could be explained by the approaches based on groundwater fluctuations. Simple and more complex methods performed similarly. For some of the approaches, there were indications that erroneous assumptions compensated each other (e.g., when overestimated recharge counteracted underestimated storage change). We found that the usage of longer time spans resulted in improved estimates of the daily recharge rates and that the estimates were further enhanced by including two night averages. When derived from fitting estimates of recharge or evapotranspiration with according measurements the specific yield, needed to convert changes in water level to water volumes, differed considerably among the methods (from 0.022 to 0.064). Thus, the specific yield can be seen as “correction factor” that compensates for inadequate process descriptions.
Reproduction of Black Drum, Pogonias cromis, from the Chesapeake Bay Region

Ovaries of black drum, Pogonias cromis, collected fromthe Chesapeake Bay region in 1992, were used to describe reproductive strategy and fecundity. Histological examination showed that black drum spawn in the Chesapeake Bay region from April through early June. Distributions of oocyte diameter showed distinct oocyte-developmental groups indicating that Chesapeake Bay black drum are group-synchronous batch spawners. Female black drum are extremely fecund ranging from 414,000 to 3,736,000 hydrated oocytes (mean = 1,389,000) per batch with a spawning periodicity of 3.8 days. Estimates of spawning strategy, spawning periodicity, and batch fecundity for black drum from the Chesapeake Bay region were similar to reported estimates from the Gulf of Mexico. INTRODUCTION In U.S. waters, where the primary range for black drum, Pogonias cromis, in the Northwest Atlantic is from the Delaware . Bay south to Florida and through the Gulf of Mexico (Welsh and Breder, 1923; Hildebrand and Schroeder, 1928; Silverman, 1979), there are at least two known populations: one along the U.S. East Coast and one or more in the Gulf of Mexico (Gold et al. 1995; Jones and Wells 1998). Many essential elements of the reproductive life history are well understood for stocks in the Gulf of Mexico (Fitzhugh et al. , 1993; Nieland and Wilson, 1993; Saucier and Baltz, 1993; Fitzhugh and Beckman, 1987). Specifically, black drum fromthe Gulf of Mexico mature at five years, are group-synchronous spawners, with a batch fecundity of 1.4 to 1.6 million hydrated oocytes, and have a spawning periodicity of 3 4 days (Fitzhugh et al. , 1993; Nieland and Wilson, 1993). In contrast to the Gulf of Mexico black drum, littl~ is known about the reproductive biology of black drum along the U.S. East Coast. Studies of adult black drum in Eastern Florida and in the Chesapeake Bay have been limited to estimating the age at maturity and spawning season. Murphy and Taylor (1989) showed that the age at first maturity is five to six years and the spawning season along Northeast Florida is from January to May with peak spawning in March and April, while Alshuth and Gilmore ( 1995) found a more protracted spawning season from October to late March. In Virginia waters Bobko (1991) observed a spawning season of April through May, and noted that all fish were mature by age six. Although the length of the spawning season and age of maturity have been documented, spawning strategy has not been described nor batch fecundity estimated for black drum from along the U.S. East Coast. Estimates of batch fecundity are essential to understanding life-time reproductive output. However, this information is difficult to obtain because an age-specific migration pattern exists for this population. Although black drum of all ages are present E-mail : bkwellswork@cs.com
An overview of the antiretroviral market

Purpose of reviewAn understanding of the current state of the antiretroviral marketplace is an important context in which to consider drug optimization work. Recent findingsThe antiretroviral marketplace has undergone a remarkable evolution over the past 11 years, expanding from serving less than 300 000 patients in low and middle-income countries in 2002 to almost 10 million patients today. In addition to dramatic growth, a steady and rapid improvement in the drugs and drug regimens used to treat patients has characterized a rapidly changing market. SummaryThe antiretroviral marketplace has been characterized by rapid growth and a succession of improving drugs and regimens over the past 11 years. The dynamic and innovative marketplace provides a strong platform from which to introduce new, optimized drugs and regimens to better serve patients’ health needs.
Cloning and sequence analysis of dehydroascorbate reductase gene (dhar) from strawberry by SON-PCR.

Dehydroascorbate reductase (DHAR) play an important role in regenerateing ascorbic acid (AsA), since it can catalyzes ascorbic acid oxidized form dehydroascorbate (DHA) to AsA. In this study, we cloned dhar gene from strawberry by SON-PCR, named Fadhar. And Fadhar is 1374 bp length, including a full ORF of 887 bp, which encoding a deduced protein of 190 amino acids with a molecular weight of 20.987 kDa and a pI of 6.24. The coding region of Fadhar is interrupted with three introns of high AT content. Homology analysis of deduced amino acid sequence on the Fadhar showed that it shared high homology with different plants species, among which it shared the highest sequence homology with Malus×domestica and the lowest with Brassica oleracea.
Inflammatory Mediators Alter Interleukin-17 Receptor, Interleukin-12 and -23 Expression in Human Osteoarthritic and Rheumatoid Arthritis Synovial Fibroblasts: Immunomodulation by Vasoactive Intestinal Peptide

Aims: To assess the contribution of fibroblast-like synoviocytes (FLS) to the inflammatory joint microenvironment under different pathogenic stimuli and their potential to respond to interleukin (IL)-17 and to determine whether the neuroimmunomodulatory vasoactive intestinal peptide (VIP) is able to modulate IL-17 receptor (IL-17R) and related cytokines. Methods: The effect of proinflammatory cytokines [tumor necrosis factor α (TNFα) and IL-17] and Toll-like receptor (TLR) ligands [poly(I:C) and lipopolysaccharide (LPS)] on IL-17R expression and IL-12 and IL-23 production was studied in osteoarthritis (OA)- and rheumatoid arthritis (RA)-FLS, involved in Th1/Th17 differentiation. The effect of VIP was also determined. IL-17RA, IL-17RC, IL-12p35 and IL-23p19 expression was measured by real-time polymerase chain reaction. IL-12 and IL-23 protein levels were measured by ELISA in supernatant cultures. Results: TNFα, LPS and poly(I:C) induced an increase in IL-17RA in RA-FLS, whereas TNFα, TNFα plus IL-17 and poly(I:C) enhanced IL-17RC transcripts in FLS. VIP diminished the upregulated expression of IL-17RA in RA-FLS following TNFα and poly(I:C). TNFα, LPS and poly(I:C) increased IL-12 and IL-23 levels in cells derived from patients presenting both pathologies. However, IL-17A decreased IL-12 and augmented IL-23. VIP decreased IL-12p35 mRNA upregulation by poly(I:C) and IL-23p19 transcripts in LPS-treated FLS. Conclusions: Inflammatory cytokines and TLR ligands modulate IL-17R, IL-12 and IL-23 possibly favoring the cross talk between FLS and Th1/Th17 cells. The ability of VIP to counteract the enhancing effect of proinflammatory molecules on IL-17R and the IL-12 family of cytokines corroborates and amplifies the beneficial effect of this endogenous neuroimmunopeptide in rheumatic diseases.
Thoracic Biometrics – Investigations of the Human Heartbeat as a Biometric : Heart Sounds , Electrocardiogram , and Vibrometry

The goals of this research project were to determine biometric performance measurements for the acoustic, electrical and pulse signals produced by the heart, referred to as thoracic signals, and to identify if a relationship exists between the electrical and pulse signals. Prior work by other research groups exist which addresses the first goal however, to our knowledge, there are no publications that address the second goal.