Miracle-dz/UniFAR-FTUs huggingface dataset:
3D HYDRODYNAMIC PRESSURE IN GAP HEIGHT DIRECTION FOR CYLINDRICAL BEARING VISCOELASTIC LUBRICATION

In this paper we show the new method of solving the lubrication problem for visco-elastic oils occurring in cylindrical micro-bearing gap. In this method are taking into account all viscoelastic terms without simplifications. In the method presented in this paper for lubricants with non-Newtonian visco-elastic properties are questioning the hitherto prevailing assumptions using in hydrodynamic theory of lubrication such as for example constant value of the hydrodynamic pressure in gap height direction. The objective of the research under the paper topic is an analytical, unified formulation and a new view of general a non-classical solution of hydrodynamic problem of microbearing lubrication using algorithm to determine oil viscoelastic properties of the lubricant and the 3D hydrodynamic pressure distribution taking into account pressure changes in gap height direction.Up to now the complete influences of non-Newtonian visco-elastic oil features on the 3D hydrodynamic pressure distribution in cylindrical microbearing gap were not considered in analytical way. We assume viscous and complete visco-elastic non-Newtonian lubricant directly near the cooperating surfaces. Viscoelastic oil properties are described by means of total form of Rivlin-Ericksen constitutive relations without simplifications.During the solution process the oil velocity components and hydro dynamic pressure are derived. The equation of motion are considered in cylindrical coordinates. Present paper elaborates the analytical method of oil velocity, pressure and friction forces determination for cylindrical slide micro-bearing. In this paper are derived the analytical formulae for velocity components, pressure distributions, in cylindrical micro-bearings.
Coordination and Efficiency in Decentralized Collaboration

Environments for decentralized on-line collaboration are now widespread on the Web, underpinning open-source efforts, knowledge creation sites including Wikipedia, and other experiments in joint production. When a distributed group works together in such a setting, the mechanisms they use for coordination can play an important role in the effectiveness of the group’s performance. Here we consider the trade-offs inherent in coordination in these on-line settings, balancing the benefits to collaboration with the cost in effort that could be spent in other ways. We consider two diverse domains that each contain a wide range of collaborations taking place simultaneously — Wikipedia and GitHub — allowing us to study how coordination varies across different projects. We analyze trade-offs in coordina- tion along two main dimensions, finding similar effects in both our domains of study: first we show that, in aggregate, high-status projects on these sites manage the coordination trade-off at a different level than typical projects; and second, we show that projects use a different balance of coordination when they are “crowded,” with relatively small size but many participants. We also develop a stylized theoretical model for the cost-benefit trade-off inherent in coordination and show that it qualitatively matches the trade-offs we observe between crowdedness and coordination.
Thumbs-up scale and frequency of use scale for use in self reporting of children's computer experience

A Computer Experience questionnaire was piloted with 49 children to validate two new scales of measurement, the Thumbs-Up Scale (TUS) and Frequency of Use Scale (FUS). TUS is a VAS (Visually Analogue Scale) designed to measure perceived skill levels. FUS is a Likert scale for measuring how often a device is used or an event occurs. The two scales gained high correlation with their respective validation measures (TUS r=.892, FUS r=.744) indicating that TUS and FUS can be used effectively with children as young as 7 years old.
Orchestration of lymphocyte chemotaxis by mitochondrial dynamics

Lymphocyte traffic is required to maintain homeostasis and perform appropriate immunological reactions. To migrate into inflamed tissues, lymphocytes must acquire spatial and functional asymmetries. Mitochondria are highly dynamic organelles that distribute in the cytoplasm to meet specific cellular needs, but whether this is essential to lymphocyte functions is unknown. We show that mitochondria specifically concentrate at the uropod during lymphocyte migration by a process involving rearrangements of their shape. Mitochondrial fission facilitates relocation of the organelles and promotes lymphocyte chemotaxis, whereas mitochondrial fusion inhibits both processes. Our data substantiate a new role for mitochondrial dynamics and suggest that mitochondria redistribution is required to regulate the motor of migrating cells.
Journal of the American Statistical Association Bayesian Inference for Logistic Models Using Pólya–gamma Latent Variables Bayesian Inference for Logistic Models Using P ´ Olya–gamma Latent Variables

Taylor & Francis makes every effort to ensure the accuracy of all the information (the " Content ") contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. We propose a new data-augmentation strategy for fully Bayesian inference in models with binomial likelihoods. The approach appeals to a new class of Pólya–Gamma distributions, which are constructed in detail. A variety of examples are presented to show the versatility of the method, including logistic regression, negative binomial regression, nonlinear mixed-effect models, and spatial models for count data. In each case, our data-augmentation strategy leads to simple, effective methods for posterior inference that (1) circumvent the need for analytic approximations, numerical integration, or Metropolis–Hastings; and (2) outperform other known data-augmentation strategies, both in ease of use and in computational efficiency. All methods, including an efficient sampler for the Pólya–Gamma distribution, are implemented in the R package BayesLogit. Supplementary materials for this article are available online.
Laser-Ultrasound Testing of Cracks in Porcelain Insulator

Detected the cracks in porcelain insulator is a strategy to prevent failure. This study proposes a remote detect technique to inspect the cracks in on-line porcelain insulator based on laser-generation based imaging (LGBI) method. Two porcelain insulators samples A and B were designed. Samples A is a 10kv porcelain insulator work outdoors, it has five artificial notch-type defects in the cylindrical surface of porcelain insulator. Sample B is a 10kv porcelain insulator work indoor with aging cracks. All defects in two specimens were detected by laser ultrasonic visualizing inspector (LUVI). Images are quite convenient to confirm cracks morphology. The experiment proves that the cracks in porcelain insulator can be detected by LUVI system.
Power to the People : Using Deep Learning to Predict Power Relations

In this project, we use deep learning to predict power relations between individuals based on email dialogue. We present several email representations that combine lexical and non-lexical features, including number of recipients and email length. Then, we construct and tune a multi-layer neural net, RNN-LSTM, and CNN to generate predictions that are tested against a formal organizational hierarchy. Experiments conducted using the Enron Email Dataset show that our best model is able to consistently outperform existing machine learning frameworks for the task.
Iodine deficiency in pregnant women living in the South East of the UK: the influence of diet and nutritional supplements on iodine status

Iodine is a key component of the thyroid hormones which are crucial for brain development. Adequate intake of iodine in pregnancy is important as in utero deficiency may have lifelong consequences for the offspring. Data on the iodine status of UK pregnant women are sparse, and there are no such data for pregnant women in the South East of the UK. A total of 100 pregnant women were recruited to a cross-sectional study carried out at the Royal Surrey County Hospital, Guildford, at their first-trimester visit for an ultrasound scan. The participants provided a spot-urine sample (for the measurement of urinary iodine concentration (UIC) and creatinine concentration) and 24 h iodine excretion was estimated from the urinary iodine:creatinine ratio. Women completed a general questionnaire and a FFQ. The median UIC (85·3 μg/l) indicated that the group was iodine deficient by World Health Organisation criteria. The median values of the iodine:creatinine ratio (122·9 μg/g) and of the estimated 24 h iodine excretion (151·2 μg/d) were also suggestive of iodine deficiency. UIC was significantly higher in women taking an iodine-containing prenatal supplement (n 42) than in those not taking such a supplement (P< 0·001). In the adjusted analyses, milk intake, maternal age and iodine-containing prenatal supplement use were positively associated with the estimated 24 h urinary iodine excretion. Our finding of iodine deficiency in these women gives cause for concern. We suggest that women of childbearing age and pregnant women should be given advice on how to improve their iodine status through dietary means. A national survey of iodine status in UK pregnant women is required.
Modelling of Adhesive Forces in Nanotweezer

In nano manipulation, carbon nanotubes (CNT) mounted on the AFM tip was used for pick and place of the nano size objects. In releasing step, the van der Waals adhesive force among the object and the contact surfaces of the gripper is not still well understood. In this paper, the adhesive electrostatic force, van der Waals (VDW) force between two cantilever tips and VDW force among cantilevers and the object are considered as dominant forces to pick and place the nano object. The equations governed on nanotweezer are solved using FEM code. The effect of object size, gap size and tips length on pull-in voltage are evaluated. The presented model could be used to design the tweezers for pick and place of size-defined nano object mounted on microgripper.
Frame Preamble MAC for MultihopWireless Sensor Networks: Design and Implementation?

MAC protocols based on preamble sampling techniques offer significant energy savings for low datarate multihop wireless sensor networks by efficiently reduc ing idle listening in lightly loaded networks. However, without any particular optimization, preamble sampling protocols still consume large amounts of energy due to the overhead induced by the long preamble transmitted prior data frames. To reduce the overhead induced by the use a full length preamble, many improvements have been proposed. These proposals targeted both the cost at the receiver and that at t he transmitter. At the transmitter side, proposals tends to minimize the preamble size by means of explicit synchronization, whereas at the receiver, proposals aim at reducing the duration of listeni ng by replacing the preamble with a series of frames. In this paper, we focus on reducing the cost at the receiver si de while showing that our solution is also compatible with solutions that reduce the cost at the transmitter side. We propose a new idea that reduces overhearing further on by avoiding reception of irrelevant frames. With our idea that is based on digest information, not only unicast frames can be fi ltered but also irrelevant (redundant) broadcast frames can be avoided a priori. We show that the use of the digest information together with the sequence number field substantially increases the energ y savings of frame preamble MAC protocols. We propose two possible implementations, Micro Frame Preamble (MFP) and Zebra Frame Preamble (ZFP), in which avoiding reception of irrelevant broadcasts can be integrated. We provide an analytical framework, in which we model the lifetime of various frame preamble MAC protocols. We complete the theoretical analysis with ns2 simulation and experimental validation through implementation on the Chipcon CC 2500 evaluation kit. We analytically show that the solution based on micro frames yields
Dihydroartemisinin and its derivative induce apoptosis in acute myeloid leukemia through Noxa-mediated pathway requiring iron and endoperoxide moiety

Anti-apoptotic protein Mcl-1 plays an important role in protecting cell from death in acute myeloid leukemia (AML). The apoptosis blocking activity of Mcl-1 is inhibited by BH3-only protein Noxa. We found that dihydroartemisinin (DHA) and its derivative X-11 are potent apoptosis inducers in AML cells and act through a Noxa-mediate pathway; X-11 is four-fold more active than DHA. DHA and X-11-induced apoptosis is associated with induction of Noxa; apoptosis is blocked by silencing Noxa. DHA and X-11 induce Noxa expression by upregulating the transcription factor FOXO3a in a reactive oxygen species-mediated pathway. Interfering with the integrity of the endoperoxide moiety of DHA and X-11, as well as chelating intracellular iron with deferoxamine, diminish apoptosis and Noxa induction. AML cells expressing Bcl-xL, or with overexpression of Bcl-2, have decreased sensitivity to DHA and X-11-induced apoptosis which could be overcome by addition of Bcl-2/Bcl-xL inhibitor ABT-737. DHA and X-11 represent a new group of AML cells-apoptosis inducing compounds which work through Noxa up-regulation utilizing the specific endoperoxide moiety and intracellular iron.
Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG

Electroencephalography (EEG) is an important clinical tool and frequently used to study the brain-behavior relationship in humans noninvasively. Traditionally, EEG signals are recorded by positioning electrodes on the scalp and keeping them in place with glue, rubber bands, or elastic caps. This setup provides good coverage of the head, but is impractical for EEG acquisition in natural daily-life situations. Here, we propose the transparent EEG concept. Transparent EEG aims for motion tolerant, highly portable, unobtrusive, and near invisible data acquisition with minimum disturbance of a user's daily activities. In recent years several ear-centered EEG solutions that are compatible with the transparent EEG concept have been presented. We discuss work showing that miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain sources. We also describe the cEEGrid flex-printed sensor array, which enables unobtrusive multi-channel EEG acquisition from around the ear. In a number of validation studies we found that the cEEGrid enables the recording of meaningful continuous EEG, event-related potentials and neural oscillations. Here, we explain the rationale underlying the cEEGrid ear-EEG solution, present possible use cases and identify open issues that need to be solved on the way toward transparent EEG.
A continuous speech recognition system integrating additional acoustic knowledge sources in a data-driven beam search algorithm

The paper presents a continuous speech recognition system which integrates an additional acoustic knowledge source into the data-driven beam search algorithm. Details of the object oriented implementation of the beam search algorithm will be given. Integration of additional knowledge sources is treated within the flexible framework of Dempster-Shafer theory. As a first example, a rule-based plosive detector is added to the baseline system.
Three-dimensional foveal shape changes after asymptomatic macular posterior vitreous detachment

Purpose To show a case in which the shape of the fovea changed after an asymptomatic macular posterior vitreous detachment (PVD). Methods The foveal shape was determined from the spectral-domain optical coherence tomography (OCT) images before and after a spontaneous macular PVD. Results A 66-year-old man with a unilateral macular hole in the right eye presented with a perifoveal PVD in the asymptomatic left eye. One year later, the left eye developed a macular PVD, and OCT measurements showed a 16.7% decrease in the central foveal thickness, and increases in the pit depth by 20.5%, foveola diameter by 14.7%, and pit volume by 19.4%. The thicknesses of the macular subfields of the Early Treatment Diabetic Retinopathy Study were decreased by 13.0% in the central subfield and by 1.4%–6.6% in the other subfields. Conclusion The deepening and widening of the fovea after a macular PVD indicate that a PVD can alter the shape of the fovea.
Improving Distantly Supervised Extraction of Drug-Drug and Protein-Protein Interactions

Relation extraction is frequently and successfully addressed by machine learning methods. The downside of this approach is the need for annotated training data, typically generated in tedious manual, cost intensive work. Distantly supervised approaches make use of weakly annotated data, like automatically annotated corpora. Recent work in the biomedical domain has applied distant supervision for protein-protein interaction (PPI) with reasonable results making use of the IntAct database. Such data is typically noisy and heuristics to filter the data are commonly applied. We propose a constraint to increase the quality of data used for training based on the assumption that no self-interaction of real-world objects are described in sentences. In addition, we make use of the University of Kansas Proteomics Service (KUPS) database. These two steps show an increase of 7 percentage points (pp) for the PPI corpus AIMed. We demonstrate the broad applicability of our approach by using the same workflow for the analysis of drug-drug interactions, utilizing relationships available from the drug database DrugBank. We achieve 37.31% in F1 measure without manually annotated training data on an independent test set.
Mining the Content of Relational Databases to Learn Ontologies with Deeper Taxonomies

Relational databases are valuable sources for ontology learning. Previous work showed how precise ontologies can be learned from such structured input. However, a major persisting limitation of the existing approaches is the derivation of ontologies with flat structure that simply mirror the schema of the source databases. In this paper, we present the RTAXON learning method that shows how the content of the databases can be exploited to identify categorization patterns from which class hierarchies can be generated. This fully formalized method combines a classical schema analysis with hierarchy mining in the data. RTAXON is one of the methods implemented in the RDBToOnto tool.
Effect of High Pressure Processing on the Thermal and Mechanical Properties of Polyethylene Films Measured by Dynamical Mechanical and Tensile Analyses

This study investigated the influence of high pressure processing on the thermal and mechanical properties of low‐density polyethylene (LDPE) films used for food packaging. This was carried out by monitoring the thermal and mechanical properties of the materials before and after the pressure treatments. Pouches made from the LDPE films were pressured at 200, 400 and 800 MPa for 5 and 10 min at 25 and 75°C. The storage and loss moduli, tensile strength and elongation at break and yield of the film samples were then measured using dynamic mechanical analysis (DMA) and an Instron® Universal Tester (Canton, MA, USA), respectively. The DMA was performed at −130 to 85°C, whereas the tensile and elongation analyses were carried out at room temperature. Results of the DMA experiments showed that the storage modulus increased with increasing pressure intensity. The tensile analysis showed that the tensile strength increased but the elongation decreased with increasing pressure treatment. Copyright © 2013 John Wiley & Sons, Ltd.
A Flexible Infrastructure for Multilevel Language Engineering

Although domain-specific modeling tools have come a long way since the modern era of model-driven development started in the early 1990s and now offer an impressive range of features, there is still significant room for enhancing the flexibility they offer to end users and for combining the advantages of domain-specific and general-purpose languages. To do this, however, it is necessary to enhance the way in which the current generation of tools view metamodeling and support the representation of the multiple, ? ontological? classification levels that often exist in subject domains. State-of-the-art tools essentially allow users to describe the abstract and concrete syntaxes of a language in the form of metamodels and to make statements in that language in the form of models. These statements typically convey information in terms of types and instances in the domain (e.g., the classes and objects of UML), but not in terms of types of types (i.e., domain metaclasses), and types of types of types, and so on, across multiple classification levels. In essence, therefore, while they provide rich support for ? linguistic? metamodeling, the current generation of tools provides little if any built-in support for modeling ? ontological? classification across more than one type/instance level in the subject domain. In this paper, we describe a prototype implementation of a new kind of modeling infrastructure that, by providing built-in support for multiple ontological as well as linguistic classification levels, offers various advantages over existing language engineering approaches and tools. These include the ability to view a single model from the perspective of both a general-purpose and a domain-specific modeling language, the ability to define constraints across multiple ontological classification levels, and the ability to tie the rendering of model elements to ontological as well as linguistic types over multiple classification levels. After first outlining the key conceptual ingredients of this new infrastructure and presenting the main elements of our current realization, we show these benefits through two small examples.
Characteristic ideals and Iwasawa theory

Let $\L$ be a non-noetherian Krull domain which is the inverse limit of noetherian Krull domains $\L_d$ and let $M$ be a finitely generated $\L$-module which is the inverse limit of $\L_d$-modules $M_d\,$. Under certain hypotheses on the rings $\L_d$ and on the modules $M_d\,$, we define a pro-characteristic ideal for $M$ in $\L$, which should play the role of the usual characteristic ideals for finitely generated modules over noetherian Krull domains. We apply this to the study of Iwasawa modules (in particular of class groups) in a non-noetherian Iwasawa algebra $\Z_p[[\Gal(\calf/F)]]$, where $F$ is a function field of characteristic $p$ and $\Gal(\calf/F)\simeq\Z_p^\infty$.