gebhart/patrepeval huggingface dataset:
Clinical application of human CD4<sup>+</sup>CD25<sup>+</sup>regulatory Tcells for the treatment of inflammatory bowel diseases (2005)

As our understanding of the immunological and genetic basis of inflammatory bowel disease (IBD) grows, potential therapeutic options are being developed at a rapid pace. Nevertheless, new drugs for IBD are needed because about half of all patients with severe ulcerative colitis (UC) eventually undergo colectomy, and a significant part of Crohn’s disease (CD) patients do not respond to standard medical therapies, including immunosuppressants and TNF-α neutralising antibodies, or suffer from significant side effects. Finally, recurrence of disease activity following remission is fr-equent in both UC and CD, and there is an unmet need for effective maintenance strategies. It is well-known that immune responses in the intestine remain in a state of controlled inflammation, suggesting that not only does active suppression by regulatory T (TR) cells play an important role in the n-ormal intestinal homeo-stasis, but also its dysregulation might lead to the development of IBD. TRcells are functional subsets of T cells that downregulate adaptive immune responses by interfering with the activation of de-ndritic cells and proliferation of T cells. From experimental work it is now clear that TR cells play a c-ritical role in maintaining immune homeostasis, and several therapeutic approaches have been targeted at the induction of TRcells in order to control mucosal inflammation. Before using TR cells clinically as living immunosuppressants for the treatment of IBD, however, we have to pass many critical checkpoints, such as the invitro expansion of TRcells and the confirmation of their safety. This paper will discuss recently gained knowledge of human TR cells and the possibility of their clinical usages as a new strategy for the treatment of IBD.
Production and characterisation of a biosurfactant isolated from Pseudomonas aeruginosa UW-1 (1997)

Pseudomonas aeruginosa UW-1 produced 17-24 g L-1 rhamnolipid in vegetable oil-containing media in shake flask cultures in 13 days. In time course studies of growth and rhamnolipid production in a salts medium containing 6% canola oil, total bacterial count reached 2.6 x 10(10) CFU ml-1 after 48 h and a maximum rhamnolipid yield of 24.3 g L-1 was obtained after 9 days. Rhamnolipid components were purified and separated by chloroform-methanol extraction and TLC chromatography. The major rhamnolipid components were characterised as L-rhamnosyl-beta-hydroxydecanoyl-beta-hydroxydecanoate and L-rhamnosyl-L-rhamnosyl-beta-hydroxydecanoyl-beta-hydr oxydecanoate by nuclear magnetic resonance and mass spectrometry. The components were separated preparatively by silica gel column chromatography. The recovered monorhamnosyl fraction contained no dirhamnosyl moiety while the recovered dirhamnosyl fraction contained 5% of the monorhamnosyl moiety when analyzed by HPLC. The ratio of mono- to dirhamnosyl components produced by P. aeruginosa UW-1 was determined by HPLC to be 4:1 by weight. Purified mono- and dirhamnosyl components had the same CMC value of 40 micrograms ml-1 and decreased the surface tension of water to 27.7 and 30.4 dynes cm-1, respectively.
What Motivates People? A Value Perspective on Interactive Workplace Spirituality (2011)

Workplace spirituality from the organizational perspective could be seen as an integrative mechanism that motivates employees towards the organizational values and mission and enhancing the commitment to them. Past studies, though affirmed its relevance and importance, were generally based on the assumption of acceptance, where the motivational goals were neglected. This study aimed to understand more on the motivational goals that promote the interaction of spirituality and its acceptance, from the value perspective, especially in a multi-culture and religion context. This research used the qualitative research method by abstracting the possible motivational goals based on the value type framework of Schwartz (1994). An in-depth interview was conducted with the employees of a religious run hospital in a multi-culture and religion context. The findings shown the value types were applicable framework for organizational spirituality, where the acceptance and participation of workplace spirituality was a process driven by diverse motivational goals. The values involved were varied, complex and possibly inconsistent. Spirituality type, which appealed directly to the spiritual needs, could be treated as separate value type in contrasting to other value types and could be discriminated without much difficulty. The perception of value was critical when there were divergence and conflict of values. This was because identification could be viewed as employees' perception of ”oneness” with the organization, and strong identification would tend to be more supportive, making decisions more consistent with the organizations' objective, consequently more involved with the mission. This study simultaneously provided a possible framework for the better understanding of what motivate the acceptance of organization spirituality, and possible directions for better integration of organizational values that is crucial for achieving the organizational goal and mission.
QoS framework for wireless IP networks (2004)

This paper proposes a novel programmable framework for QoS support in wireless IP networks. The framework is based on classification of IP traffic into two main classes, A and B, where class-A is further divided into three subclasses. It consists of three main modules: packet classifier, scheduler and admission control module. Packets are classified at network nodes by using differentiated services. Different classes are serviced using priorities. The scheduling is adaptive. For a real time flow, such as CBR and VBR, it adapts to location-dependent bit-errors in the wireless channel by increasing bandwidth share of the affected flow until it reaches its effective throughput. Admission control module is made programmable, providing possibility to reserve part of the bandwidth for lower priority classes to avoid monopolization of the wireless link by higher priority classes.
Densely Connected Pyramid Dehazing Network (2018)

We propose a new end-to-end single image dehazing method, called Densely Connected Pyramid Dehazing Network (DCPDN), which can jointly learn the transmission map, atmospheric light and dehazing all together. The end-to-end learning is achieved by directly embedding the atmospheric scattering model into the network, thereby ensuring that the proposed method strictly follows the physics-driven scattering model for dehazing. Inspired by the dense network that can maximize the information flow along features from different levels, we propose a new edge-preserving densely connected encoder-decoder structure with multi-level pyramid pooling module for estimating the transmission map. This network is optimized using a newly introduced edge-preserving loss function. To further incorporate the mutual structural information between the estimated transmission map and the dehazed result, we propose a joint-discriminator based on generative adversarial network framework to decide whether the corresponding dehazed image and the estimated transmission map are real or fake. An ablation study is conducted to demonstrate the effectiveness of each module evaluated at both estimated transmission map and dehazed result. Extensive experiments demonstrate that the proposed method achieves significant improvements over the state-of-the-art methods. Code will be made available at: https://github.com/hezhangsprinter
The function of semantics in automated language processing (1971)

This paper is a survey of some of the major semantic models that have been developed for automated semantic analysis of natural language. Current approaches to semantic analysis and logical inference are based mainly on models of human cognitive processes such as Quillian's semantic memory, Simmon's Protosynthex III and others. All existing systems and/or models, more or less experimental, were applied to a small subset of English. They are highly tentative because the definitions of semantic processes and semantically structured lexicons are not formulated rigorously. This is due mainly to the fact that it is unknown whether a unique, consistent hierarchization of the semantic features of language is possible.However, the models described are significant contributions to an unexplored field called semantics. The progressive development of a sophisticated, semantically based system for automated processing of natural language is a realistic goal. It should not be neglected, despite the fact that it is difficult to predict when this goal will be achieved.
Non-steroidal anti-inflammatory drugs for the common cold (2015)

NSAIDs are somewhat effective in relieving the discomfort caused by a cold but there is no clear evidence of their effect in easing respiratory symptoms. The balance of benefit and harms needs to be considered when using NSAIDs for colds.
[Management of prolactinomas during pregnancy]. (2002)

Discontinuing dopamine agonists is safe during pregnancy for microadenoma. The risk of macroadenoma enlargement during pregnancy is high. Regular visal field testing is necessary during pregnancy. Prolactinoma doesn't influence gestation complication and fetus.
Parallel MR image reconstruction by adaptively weighted H<inf>&#x221E;</inf> optimization (2009)

H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> optimal reconstruction [1] is a new method we recently proposed to overcome the difficulties in SENSE reconstruction of parallel MRI when the coil sensitivity map is uncertain and ill-conditioned. However, the weighting selection in this method is ad hoc and may involve tedious trial and error. To overcome this problem, this paper proposes a novel adaptively weighted H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> optimal reconstruction method for image reconstruction of parallel MRI. The novelty is two folds. First, the weighting factor ß is considered as a unique adaptive value for each individual pixel instead of a global value. Second, the selection of ß is based on an optimization instead of trial and error experiments. The proposed method enhances the performance of the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> optimal reconstruction by adaptive weighting and automates the weighting selection by minimizing generalized cross validation (GCV) function.
Agronomic efficiency of NBPT as a urease inhibitor: A review (2018)

Urea is the most widely used nitrogen (N) fertilizer, with a projected increase in annual demand of 1.5% in the coming years. After its application to soil, urea undergoes hydrolysis via the urease enzyme, causing increases in the soil pH in the surrounding area of the granules and resulting in NH<sub>3</sub> losses that average 16% of N applied worldwide and can reach 40% or more in hot and humid conditions. The use of urease inhibitors is an effective way to reduce NH<sub>3</sub> losses. Several compounds act as urease inhibitors, but only N-(n-butyl) thiophosphoric triamide (NBPT) has been used worldwide, being the most successful in a market that has grown 16% per year in the past 10 years. Only in the past three years other compounds are being commercially launched. In comparison to urea, NBPT-treated urea reduces NH<sub>3</sub> loss by around 53%. Yield gain by NBPT usage is of the order of 6.0% and varies from -0.8 to 10.2% depending on crop species. Nitrification inhibitors usually increase NH<sub>3</sub> volatilization and mixing them with urease inhibitors partially offsets the benefits of the latter in reducing NH<sub>3</sub> loss. The efficacy of NBPT to reduce NH<sub>3</sub> loss is well documented, but there is a need for further improvement to increase the period of inhibition and the shelf life of NBPT-treated urea.
Dynamic Contextual Multi Arm Bandits in Display Advertisement (2016)

We model the ad selection task as a multi-armed bandit problem. Standard assumptions in the multi-armed bandit (MAB) setting are that samples drawn from each arm areindependent and identically distributed, rewards (or conversionrates in our scenario) are stationary and rewards feedback areimmediate. Although the payoff function of an arm is allowed toevolve over time, the evolution is assumed to be slow. Display ads, on the other hand, are regularly created while others are removed from circulation. This can occur when budgets run out, campaign goal changes, holiday season ends and many other latent factors that go beyond the control of the ad selection system. Another big challenge is that the set of available ads is often extremely huge but standard multi-armed bandit strategies converge with linear time complexity that cannot accommodate the usually dynamic changes. Due to the above challenges and the restrictions of the original MAB, we propose a novel dynamic contextual MAB which tightly integrates components of dynamic conversion rates prediction, contextual learning and arm overlapping modeling in a principled framework. Besides we propose an accompaniedmeta analyses framework that allows us to conclude experiments in a more statistically robust manner. We demonstrate on a world leading demand side platform (DSP) that our framework can effectively discriminate premium arms and significantly outperform some standard variations of MAB to these settings.
Real‐Time Consensus‐Based Scene Reconstruction Using Commodity Graphics Hardware<sup>†</sup> (2003)

Abstract We present a novel use of commodity graphics hardware that effectively combines a plane‐sweeping algorithm with view synthesis for real‐time, online 3D scene acquisition and view synthesis. Using real‐time imagery from a few calibrated cameras, our method can generate new images from nearby viewpoints, estimate a dense depth map from the current viewpoint, or create a textured triangular mesh. We can do each of these without any prior geometric information or requiring any user interaction, in real time and online. The heart of our method is to use programmable Pixel Shader technology to square intensity differences between reference image pixels, and then to choose final colors (or depths) that correspond to the minimum difference, i.e. the most consistent color. In this paper we describe the method, place it in the context of related work in computer graphics and computer vision, and present some results. ACM CSS: I.3.3 Computer Graphics— Bitmap and framebuffer operations , I.4.8 Image Processing and Computer Vision— Depth cues, Stereo
Plaidoyer pour une Italie ambiguë (1981)

Apology for an Ambiguous Italy, by Sergio Romano In Italy, foreign policies emanating from society coexist with that emanating from the State. Despite Unification, regional and "ideological" foreign policies still exist. Catholics are sympathetic to Italy's Mediterranean role whereas the Northern Italian industrial "bourgeoisie" is strongly European and pro-Western for economic and cultural reasons. Two greats currents of post-Risorgimento diplomacy have conditioned the foreign policy of the Italian government: a feeling of insecurity and a desire to affirm the role and the originality of Italy in the world. The feeling of insecurity pushes Italy to seek the protection of a powerful partner: Germany, the United Kingdom and, after 1945, the USA. The Italian government must also try to reconcile the foreign policies of its society and this explains the permanent interaction between foreign and domestic policies. But, due to the pluralism of its protagonists, Italy is much more present on the international scene than its size and political importance would warrant. The ideal world for Italian diplomacy is one in which no one moves, where its allies do not try to impose on it coherent choices. For this reason, the suggestion found in the report of the four institutes on "Western Security" that Italy only participate for Mediterranean problems is dangerous as it would oblige Italy to express only part of its history and aspirations.
Customer Adapted Maintenance Plan (CAMP): A Process for Optimization of Gas Turbine Maintenance (2008)

Maintaining high levels of availability and reliability are essential objectives for many industries, especially those that are subject to high costs due to shutdowns of critical systems, e.g. gas turbines. To utilize these systems as effectively as possible, preventive maintenance must be optimized. Determining what is optimal is, however, a multi-variable task requiring detailed knowledge about the components in the system and their different damage mechanisms. These factors have always affected the condition of the gas turbine and maintenance actions, but only recently has it been possible to estimate and measure them correctly for individual components during operation. In the past, it was necessary to construct maintenance intervals from the most critical component (or components), requiring the highest maintenance frequency. An additional worst-case scenario margin was also necessary, taking into account factors such as possible load variation, differences in environment (affecting e.g. power turbine temperatures) and other sources of uncertainty. These uncertainties together have determined traditional maintenance planning, with maintenance packages each containing a set of maintenance activities for a set of components being predetermined and preplanned. With the new CAMP approach, the maintenance strategy is to reach a Retirement For Cause (RFC) strategy, where components are not replaced until a potential failure has been detected. This requires measurement techniques that can monitor how the gas turbine is operated, prognostics capabilities that foresee maintenance needs, and test methods that can determine the state of a component during maintenance events. One important part of CAMP is therefore a prognostic tool which tells us the condition, and therefore the maintenance needs, of individual components within the gas turbine. To handle this information and efficiently make a preventive maintenance plan, software for gas turbine maintenance optimization has been developed. The software can not only calculate the most efficient point in time for a maintenance action, it can also adjust the maintenance plan to any customer’s specific demands. This paper describes the model, gathering and processing of information, risk assessment performance and the result from an optimization which groups maintenance actions as a result of customer prioritized demands. It also describes the software layout and how it is used.
Expression and activity of eIF6 trigger Malignant Pleural Mesothelioma growth<i>in vivo</i> (2015)

eIF6 is an antiassociation factor that regulates the availability of active 80S. Its activation is driven by the RACK1/PKCβ axis, in a mTORc1 independent manner. We previously described that eIF6 haploinsufficiency causes a striking survival in the Eμ-Myc mouse lymphoma model, with lifespans extended up to 18 months. Here we screen for eIF6 expression in human cancers. We show that Malignant Pleural Mesothelioma tumors (MPM) and a MPM cell line (REN cells) contain high levels of hyperphosphorylated eIF6. Enzastaurin is a PKC beta inhibitor used in clinical trials. We prove that Enzastaurin treatment decreases eIF6 phosphorylation rate, but not eIF6 protein stability. The growth of REN, in vivo, and metastasis are reduced by either Enzastaurin treatment or eIF6 shRNA. Molecular analysis reveals that eIF6 manipulation affects the metabolic status of malignant mesothelioma cells. Less glycolysis and less ATP content are evident in REN cells depleted for eIF6 or treated with Enzastaurin (Anti-Warburg effect). We propose that eIF6 is necessary for malignant mesothelioma growth, in vivo, and can be targeted by kinase inhibitors.
Big data: Issues, challenges, tools and Good practices (2013)

Big data is defined as large amount of data which requires new technologies and architectures so that it becomes possible to extract value from it by capturing and analysis process. Due to such large size of data it becomes very difficult to perform effective analysis using the existing traditional techniques. Big data due to its various properties like volume, velocity, variety, variability, value and complexity put forward many challenges. Since Big data is a recent upcoming technology in the market which can bring huge benefits to the business organizations, it becomes necessary that various challenges and issues associated in bringing and adapting to this technology are brought into light. This paper introduces the Big data technology along with its importance in the modern world and existing projects which are effective and important in changing the concept of science into big science and society too. The various challenges and issues in adapting and accepting Big data technology, its tools (Hadoop) are also discussed in detail along with the problems Hadoop is facing. The paper concludes with the Good Big data practices to be followed.
Understanding Penetration Index Measurements and Regional Lung Targeting (2012)

Radiolabeling of pharmaceutical inhalation aerosols began in the late 1970s. Since then, well over 100 studies have been published. These studies have documented lung deposition for all inhalation dosage forms; pressurized metered dose inhalers (pMDIs), dry powder inhalers (DPIs), soft mist inhalers (SMIs), and nebulizers. They have provided valuable insight into the factors that influence total and regional lung deposition. Taken globally, this collection of data has recently been used to elucidate the influence of intersubject variability in head geometry on total lung deposition, showing good correspondence between theory and experiment. The analysis reported here is an attempt to take this data set one step "deeper" into the airways and understand the relationship between P/C ratio, derived from 2D imaging, and a more anatomically relevant biological distribution within the lung, 24-h clearance. Intersubject variability in regional deposition is also analyzed, although due to the sparse nature of the reported individual data only tentative conclusions can be drawn. Many different techniques for derivation and analysis of scintigraphic data have been reported in the literature, and this leads to some difficulties when performing the "meta-analyses" reported below. In this regard it is recommended that standardization of scintigraphy techniques should be a future goal.