Miracle-dz/UniFAR-FTUs huggingface dataset:
ANALYSIS OF THE FLOW IN A PROPULSION NOZZLE SUBJECTED TO A FLUID INJECTION

The aero-thermodynamics propulsion systems is one of the fields of fluid mechanics where decisive progress is still needed to improve performance and meet the continued demand to orbit increasingly heavy payloads. It’s the chemical propulsion using the thermal energy during combustion of the propellant, which remains the most reliable way to meet the requirements of high demands for thrust, specifically to lift-off. For those of propulsion, the nozzle is the body to convert most effectively heat energy into kinetic energy of the mixture. The divergent portion of a nozzle is the seat of an exhaust gas flow at high enthalpy, where a fraction is transmitted to the wall of the divergent portion, thus altering its lifetime. The long periods of operation and the amplitude of the heat flux set the issues, require cooling technique film for the wall of the divergent portion. For weight constraints, it is a fraction of the flow of fuel supplied to the combustion chamber, which is injected into a section of the diverging form of a gaseous film adjacent to the wall. The injection conditions must be adjusted in order to avoid problems associated with outbreaks of losses and local re-inflammations. This work represents a numerical investigation of the dynamic and thermal of a compressible flow in the nozzle BKE-DLR, representing a laboratory scale model of the Volvo nozzle of the European Vulcain cryogenic engine 2. The Torque of propellants H2 / O2 is injected at 50 bar, in a mixing ratio of 6.2 in a cylindrical combustion chamber, wherein the thermodynamic conditions (pressure, temperature) are taken as reservoirs values for the flow relaxation. The axisymmetric nozzle having a ratio of 57 in its output section is subjected to a GH2 film cooling in a section where the ratio is equal to 32. Energy & Euler's equations are discretized and solved on a non-uniform structured grid, in the sense of finite volume numerical schemes with Roe type for convective terms. A zero-dimensional calculation (0D) allows the use of thermodynamic relations to predict aero-thermochemical variables in each slice of the divergent, especially in the downstream of the injection section. The compressible flow in the absence of cooling is digitally reproduced on the axisymmetric model to predict the level of thrust and the rate of loss by divergence, so that the temperature distribution in the vicinity closes to the wall of the divergent portion. The results are compared with values predicted by thermodynamic calculations. The cooling is then carried out for the two cases, sonic and supersonic for the injection port, wherein the evaluating a cooling performance index defined as a reduced temperature. The distribution of the efficiency index to a power line located downstream of the injection zone, is confronted with the measurements on the test bench (DLR). A parametric analysis is then conducted on the effects of the injection angle relative to the wall and the injected flow rate, on the level of thrust and on the cooling efficiency.
Projection Interlingue d’Étiquettes pour l’Annotation Sémantique Non Supervisée (Cross-lingual Annotation Projection for Unsupervised Semantic Tagging)[In French]

Nos travaux portent sur la construction rapide d’outils d’analyse linguistique pour des langues peu dotées en ressources. Dans une précédente contribution, nous avons proposé une méthode pour la construction automatique d’un analyseur morpho-syntaxique via une projection interlingue d’annotations linguistiques à partir de corpus parallèles (méthode fondée sur les réseaux de neurones récurrents). Nous présentons, dans cet article, une amélioration de notre modèle neuronal, avec la prise en compte d’informations linguistiques externes pour un annotateur plus complexe. En particulier, nous proposons d’intégrer des annotations morpho-syntaxiques dans notre architecture neuronale pour l’apprentissage non supervisé d’annotateurs sémantiques multilingues à gros grain (annotation en SuperSenses). Nous montrons la validité de notre méthode et sa généricité sur l’italien et le français et étudions aussi l’impact de la qualité du corpus parallèle sur notre approche (généré par traduction manuelle ou automatique). Nos expériences portent sur la projection d’annotations de l’anglais vers le français et l’italien.
The Design of a Low Power MEMS Based Micro-hotplate Device Using a Novel Nickel Alloy for Gas Sensing Applications

In this paper comparative analysis of MEMS (Micro-electro-mechanical System) based Micro-hotplate using three different heating elements use as separately are presented. Three different materials (viz. DilverP1, Polysilicon, and Platinum) are used as heating elements with same thickness of 0.2 m. CoventorWareTM simulator has been used for construction of 3D model and electro-thermo-mechanical analysis of Micro-hotplate device. Power consumption, stress and displacement of Micro-hotplate are studied at operating temperature (165 oC). It is obtained that power consumption, stress and displacement of Dilverp1 heating element are 13.06 mW, 190 MPa and 0.028 m which are less in comparison to those with Poly Silicon heater and Platinum heater at moderate temperature (150-200 C) over the sensing material (ZnO).
Feedforward and Feedback Control Share an Internal Model of the Arm ’ s Dynamics X

Recent work has shown that, when countering external forces, the nervous system adjusts not only predictive (i.e., feedforward) control of reaching but also reflex (i.e., feedback) responses to mechanical perturbations. Here we show that altering the physical properties of the arm (i.e., intersegmental dynamics) causes the nervous system to adjust feedforward control and that this learning transfers to feedback responses even though the latter were never directly trained. Forty-five human participants (30 females) performed a single-joint elbow reaching task and countered mechanical perturbations that created pure elbow motion. In our first experiment, we altered intersegmental dynamics by asking participants to generate pure elbow movements when the shoulder joint was either free to rotate or locked by the robotic manipulandum. With the shoulder unlocked, we found robust activation of shoulder flexor muscles for pure elbow flexion trials, as required to counter the interaction torques that arise at the shoulder because of forearm rotation. After locking the shoulder joint, which cancels these interaction torques, we found a substantial reduction in shoulder muscle activity over many trials. In our second experiment, we tested whether such learning transfers to feedback control. Mechanical perturbations applied to the arm with the shoulder unlocked revealed that feedback responses also account for intersegmental dynamics. After locking the shoulder joint, we found a substantial reduction in shoulder feedback responses, as appropriate for the altered intersegmental dynamics. Our work suggests that feedforward and feedback control share an internal model of the arm’s dynamics.
DEVELOPMENT OF A BIOTIC SCORE FOR THE ASSESSMENT OF THE 3 ECOLOGICAL QUALITY OF THE RIVERS AND STREAMS OF MADEIRA

Macro-invertebrate assemblages are commonly used to assess the impact of anthropogenic activity on rivers. The results are quantified and expressed as biotic index values. Many ecological assessment methods exist and the results are used in catchment management planning. Methods developed for the surface waters of continental Europe are not readily applied to Madeira because of the very low biodiversity of the Madeiran macro-invertebrate fauna. The most diverse macro-invertebrate family in Madeira is the Chironornidae with an estimated 77 species. Statistical analysis of data derived from macro-invertebrate samples . collected in 1991-92 redted in the development of an experimental biotic index, which was tested on a new independent data-set generated from a field collection programme carried out in 1997. Some results of the application of the experimental index and the Chironomid Pupal Exuviae Technique (CPET), a separate ecological assessment method, are analysed and discussed. The need for further testing and development is described.
Constituting a Musical Sign Base through Score Analysis and Annotation

The recent progress in Information and Communication Technologies has given birth to advanced applications in the field of instrumental e-learning. However, most of these applications only propose a limited number of lessons on predetermined pieces, according to the vision of a single music expert. Thus, this article introduces a web platform to create music lessons dynamically and collaboratively, with the assistance of a semi-automatic score annotation module: @-MUSE. To do so, we first describe a new methodology to design such a platform: Sign Management. Then, we detail its general architecture as an Iterative Sign Base System based on a common practice in musical learning: score annotation. Lastly, we give various algorithms to generate relevant annotations on a score in order to explain it. These algorithms are based on the analysis of musical patterns difficulty. They are implemented within a module of @-MUSE called Score Analyzer. We present here its
The MADS box of serum response factor is sufficient for induction of muscle spindle-specifying gene Egr 3

;pCoJj Under.9rad The. :. C-:>1 s LD {) 1-) £ c; . z j./ r;o; GLJ Muscle spindles are an essential part of the neuro-muscular system because they act as sensory receptors of muscle and limb position that communicate with the nervous system and sense movement. It has been established that the neuregulin1(NRG1}ErbB signaling pathway plays a key role in the formation of muscle spindles. Our research aims to further characterize this pathway and more specifically the role of the transcription factor serum response factor (SRF), which previous evidence suggests may be a downstream effector during NRG 1 signaling. To address how SRF is targeted during neuregulin signaling, we have generated muscle cells that inactivate endogenous SRF and express a truncated mutant form of SRF, using retroviral transduction and CRISPR/Cas9. These cells were then stimulated with NRGl and qRT-PCR was used to measure expression of Early growth response 3 (Egr3), which is a key target gene activated by SRF in the NRG1-ErbB pathway. In these cells, transcription ofEgr3 is induced by NRG 1 consistent with wild-type cells. These results suggest that transcriptional induction of Egr3 by NRG1 occurs independently ofthe N-and Cterminal domains ofSRF and the MADS box is sufficient for induction. Future experiments will further investigate the MADS box and its interactions with known co factors in the development of muscle spindles.
MODEL REVIEW AND SENSITIVITY ANALYSIS OF THE SÁROSPATAK RESERVOIR MODEL , NE-HUNGARY

Hungary’s favourable natural conditions for geothermal energy production and utilization are well known. The anomalously high thermal gradient and the significant expanse of deep aquifers make Hungary one of the most notable European countries regarding low-temperature geothermal resources. Among other cities, Sárospatak in northeast Hungary has utilized its deep carbonate geothermal reservoir for bathing purposes since the 1960s. In recent years, a 7-layer, threedimensional numerical model with two proposed wells for district heating was constructed by the Icelandic company Vatnaskil Consulting Engineers. The main objective was to predict the impact of the planned well duplet on the geothermal reservoir at Sárospatak with a special focus on the existing geothermal wells associated with the thermal spa of the city. In this study, after a model and literature review, a detailed sensitivity analysis with 11 different scenarios was performed. Results of the analysis show that 1) the model is not sensitive to input parameters in its lower layers, 2) the model is not sensitive to the porosity and 3) the model is very sensitive to the hydraulic conductivity in the top model layers, especially the producing layer. It has also been shown that the proposed wells are not likely to have any negative impact on the existing thermal wells. On the other hand, the study shows that the existing thermal wells could have a significant impact on the reservoir pressure at the proposed well duplet. Lack of data related to the existing thermal wells (their actual production and the exact thickness and extent of the tuff layer from which they are producing) are crucial factors preventing their actual impacts from being known. These impacts could be the key in determining the success of the Sárospatak geothermal project.
Knowledge-Driven User Behavior Model Extraction for iObserve

Modern cloud-based software systems are exposed to constant alterations due to changing requirements. These changes can be based on various reasons. Ever-changing usage patterns of the systems user-base can be one reason for changes. A shift in the user-behavior can result in increasing load on single services or have strong economic effects for e-commerce platforms. If the usage patterns are known, the software system can be analyzed and adapted. In this thesis we provide an approach to extract user-behavior from monitored operation-calls of a software system. Since user-behavior is not only dependent on the navigational pattern of the user in the system, but also on the specific information processed by the call, our focus lies on adding this information to the monitoring records. We then propose an identification of user-behavior models and clustering process for similar user-behavior patterns. These user-behavior models are using the enriched call information to improve accuracy. We implemented our approach as a pipe-and-filter based service, which is integrated into the iObserve framework. The framework provides access to the monitoring records of the system and transforms them into user-sessions. To get the call-information from the system, we extend the monitoring records to hold this data. In our service, we prepare the sessions containing user-behavior and call-information for the clustering. Then the sessions are aggregated to behavior models by a clustering algorithm.
Novel Machine Learning Identifies Brain Patterns Distinguishing Diagnostic Membership of HIV, Alcoholism, and Their Comorbidity of Individuals

Objective: The incidence of Alcohol Use Disorder (AUD) in human immunodeficiency virus (HIV) infection is twice that of the rest of the population. This study documents complex radiologically-identified, neuroanatomical effects of AUD+HIV comorbidity by identifying structural brain systems that predicted diagnosis on an individual basis. Method: Applying novel machine learning analysis to 549 participants (199 controls, 222 AUD, 68 HIV, 60 AUD+HIV), 298 MRI brain measurements were automatically reduced to small subsets per group. Significance of each diagnostic pattern was inferred from its accuracy in predicting diagnosis and performance on 6 cognitive measures. Results: While all three diagnostic patterns predicted the learning and memory score, the AUD +HIV pattern was the largest and had the highest predication accuracy (78.1%). Conclusions: Providing a roadmap for analyzing large, multimodal data sets, the machine learning analysis revealed imaging phenotypes that predicted diagnostic membership of MRIs of individuals with AUD, HIV, and their comorbidity.
Laminar viscoelastic flow through a plane sudden expansion

The results are reported of an experimental investigation of the laminar flow of a viscoelastic liquid, a 0.4% aqueous solution of polyacrylamide (Seperan AP 273 E), through a plane sudden expansion, of expansion ratio R=D/d=1.43, immediately preceded by a smooth contraction. The flow field downstream of the expansion is devoid of recirculation and this is a consequence of the viscoelasticity of the fluid damping out vortex activity. The effect of the smooth contraction is more thought provoking. The velocity profile produced by the contraction is intriguing and attempts are made to understand the physical processes generating this profile and to relate this to the viscoelasticity of the liquid.
BlockchainDB - A Shared Database on Blockchains

In this paper we present BlockchainDB , which leverages blockchains as a storage layer and introduces a database layer on top that extends blockchains by classical data management techniques (e.g., sharding) as well as a standardized query interface to facilitate the adoption of blockchains for data sharing use cases. We show that by introducing the additional database layer, we are able to improve the performance and scalability when using blockchains for data sharing and also massively decrease the complexity for organizations intending to use blockchains for data sharing. PVLDB Reference Format: Muhammad El-Hindi, Carsten Binnig, Arvind Arasu, Donald Kossmann, Ravi Ramamurthy. BlockchainDB A Shared Database on Blockchains. PVLDB, 12(11): 1597-1609, 2019. DOI: https://doi.org/10.14778/3342263.3342636
Symbiotic seed germination and seedling growth promoted by Rhizoctonia fungi in Cymbidium mastersii , an endangered orchid species endemic to Southwest of China

The presence of appropriate fungal mycobiont for seedling recruitment and plant nutritional support is essential for the long-term survival of orchids in managed or restored habitats. In order to screen mycorrhiza fungus that can promote the seed germination and form the symbiosis with Cymbidium mastersii Griff.ex Lindl and scale produce high quality seedling, we first symbiosis cultivated seeds with different fungi in the medium of cortices symbiotic culture, then measured the biomass of seedlings, re-separation of fungus strain, studied the 3D hypha net by using the optical microscope and electron microscope, and determined the seed vitality with TTC method. The results showed that strain CLB111 and MLX102 that were separated from roots of Cymbidium goeringii Rchb f. and C. sinense Willd can promote the seed germination of Cymbidium mastersii. The differences of germination rates between treatments with strain symbiosises and control were significant. Re-separations from the culture medium confirmed the strains in symbiosis roots were the same as the inoculated strains.The optical microscope and electron microscope observation found that many fungus hypha infected into embryo cell and formed the 3D hypha net, and the embryo started differentiation.TTC measurement showed that the seed had high vitality. No strain was found by re-separation from culture medium, no hypha was observed and very low vitality under control treatment. Thus, it can be concluded that strain CLB111 and MLX102 can form the symbiosis and promote the seed germination of Cymbidium mastersii. The experiments found the fungus separated from adult orchids and the fungus that promote the seed germination were the same strains in Cymbidium mastersii. This phenomenon was different from the Gastrodia elata Blume. It was also confirmed that funguses that can form symbiosis with and promote the seed germination of Cymbidium mastersii were not absolutely specific. Under certain condition, different strains can significantly promote germination of one orchid species. It may need further investigation to verify the differences under different ecological conditions.
MINERAL COMPOSITION OF HERBY CHEESE PRODUCED FROM RAW AND PASTEURIZED MILK

In this study, the effects of sirmo (Allium vineale L.), mendi (Chaerophyllum macropodum Boiss.) and siyabo (Ferula rigidula DC.) on mineral compositions of herby cheese produced from raw and pasteurized milk in brine and vacuum package during 90 days ripening were determined. Macroelements (Ca, Mg, Na, K) and micro elements (Fe, Zn, Mn) concentration of herby cheese samples were examined by Inductively Coupled Plasma-Optical Emission Spectrometer (ICP-OES). It was determined that the mineral concentration was changed from highest to lowest Na>Ca>K>Mg>Zn>Fe>Mn in the herby cheese. The highest mean concentration of Na was found in Sirmo added cheeses manufactured from raw milk in brine on the second day of ripening and the lowest mean concentration of Mn was found in Sirmo added cheeses produced from pasteurized milk in brine at the end of 90 days. Na, Ca, K, Mg, Zn, Fe and Mn content of cheeses in brine and vacuum package decreased during ripening period.
Evaluation of a learning outcomes taxonomy to support autonomous classification of instructional activities

With an increased focus on assuring the quality of student achievement in higher education, there is a commensurate need for tools to assist academics in understanding the nature of assessment and how it can provide evidence of student learning outcomes. This paper describes research conducted the Instructional Activity Matrix; a taxonomy that was developed as the basis of a learning support tool, Maestro, that automatically analyses outcomes and assessment statements to show the cognitive level and nature of knowledge inherent in them. Findings indicate that the matrix is a valid tool for defining the nature of learning outcomes and had value in clarifying the nature of assessment and outcomes. However, issues identified with the inherent ambiguity of some instructional statements and their contextually-laden language provided insights into how Maestro will need to be refined to provide appropriate support for teachers, with a range of experience across multiple disciplines.
4 An Interfacial Thermodynamics Model for Protein Stability

Proteins are important macromolecules that exhibit thermodynamic and kinetic properties that are highly tuned to facilitate biological function within limited ranges of environmental conditions. Despite having a wealth of understanding of the interactions that affect protein stability [Dill, 1990; Pace, et al. 2004], such as the hydrophobic effect, hydrogen bonding, packing, solvation and electrostatic effects: Predicting thermodynamic properties of proteins is difficult because these interactions simultaneously work together within the molecular structure comprising of heterogeneous microenvironments that change dynamically as the conformational state of the protein changes. Consequently, a protein is truly a complex system [Bar-Yam, 1997] where thermodynamic and other emergent physical properties are sensitive to small perturbations in protein structure or its environment. It remains an open problem to develop models that can accurately predict protein stability, ligand-protein binding affinities and allosteric response, all of which are critical to the function of a protein [Petsko & Ringe, 2004; Klepeis, et al. 2004; Bray & Duke, 2004].