Miracle-dz/UniFAR-FTUs huggingface dataset:
Bingham plastic fluid flow model in tape casting of ceramics using two doctor blades – analytical approach

Abstract One of the most common processes used in manufacturing of multilayer ceramic packages, multilayer capacitors and large scale integration circuits is tape casting. In this process, the wet tape thickness is one of the single most determining parameters affecting the final properties of the product, and it is therefore of great interest to be able to control it. One way to control the tape thickness is to use a two doctor blade configuration in the tape casting machine. In this case, it becomes important to fix the height of the slurry in front of both doctor blades according to the desired tape thickness and casting speed (belt velocity). In the present work, the flow in both doctor blade regions of a slurry is described with a steady state momentum equation in combination with a Bingham plastic constitutive equation, and this is integrated to a closed form analytical solution for both reservoirs based on the desired wet tape thickness and casting speed. The developed model is used to investigate the impact of different material parameters and machine designs on the required slurry height. The solution is compared with experimental findings from the literature, and good agreement is found.
Gemma in April: A matrix-like parallel programming architecture on OpenCL

Nowadays, Graphics Processing Unit (GPU), as a kind of massive parallel processor, has been widely used in general purposed computing tasks. Although there have been mature development tools, it is not a trivial task for programmers to write GPU programs. Based on this consideration, we propose a novel parallel computing architecture. The architecture includes a parallel programming model, named Gemma, and a programming framework, named April. Gemma is based on generalized matrix operations, and helps to alleviate the difficulty of describing parallel algorithms. April is a high-level framework that can compile and execute tasks described in Gemma with OpenCL. In particular, April can automatically 1) choose the best parallel algorithm and mapping scheme, and generate OpenCL kernels, 2) schedule Gemma tasks based on execution costs such as data storing and transferring. Our experimental results show that with competitive performance, April considerably reduces the programs' code length compared with OpenCL.
Auger and x-ray photoelectron spectroscopy

Perspective on the Analysis of Surfaces and Interfaces Instrumentation Spectral Interpretation Depth Profiling in AES and XPS Quantification of AES and XPS Applications of AES in Microelectronics AES in Metallurgy Applications of Electron Spectroscopy to Heterogeneous Catalysis Applications of XPS in Polymer Technology Uses of Auger Electron and Photoelectron Spectroscopies in Corrosion Science.
Boundary second-order sliding-mode control of an uncertain heat process with spatially varying diffusivity

The primary concern of the present paper is the regulation of an uncertain heat process with collocated boundary sensing and actuation. The underlying heat process is governed by an uncertain parabolic partial differential equation (PDE) with mixed boundary conditions. The process exhibits an unknown spatially varying diffusivity parameter, and is affected by a smooth uncertain boundary disturbance which is, possibly, unbounded in magnitude. The proposed robust synthesis is formed by the linear feedback design and by the “Twisting” second-order sliding-mode control algorithm, suitably combined and re-worked in the infinite-dimensional setting. A non-standard Lyapunov functional is invoked to prove the global asymptotic stability of the resulting closed-loop system in a suitable Sobolev space. The proof is accompanied by a set of simple tuning rules for the controller parameters. The effectiveness of the developed control scheme is supported by simulation results.
Analysis of risk dynamics in information technology service delivery

Purpose – The purpose of this paper is to define and analyse risks within information technologies (IT) in service delivery. Some specific risks that appear in IT service delivery and the relationships between risks will be defined. The objective of the study is to advance understanding of risks and their effects on specific processes within the delivery of IT services.Design/methodology/approach – Risks were determined by reviewing processes in International Business Machines (IBM), by taking the Information Technologies Infrastructure Library (ITIL) as a basis, which is a standard in IT, and with the help of the Information Technology Service Management (ITSM) Metrics Model. The ITSM Metrics Model is actually used for finding delay times for specific processes and determining specific risks. ITIL is used to decide on the most risky processes for IT delivery. According to observations and some interviews with employees at IBM Service Delivery, the risk level is defined by the percentage of impact of spec.
Similarity based Dynamic Web Data Extraction and Integration System from Search Engine Result Pages for Web Content Mining

There is an explosive growth of information in the World Wide Web thus posing a challenge to Web users to extract essential knowledge from the Web. Search engines help us to narrow down the search in the form of Search Engine Result Pages (SERP). Web Content Mining is one of the techniques that help users to extract useful information from these SERPs. In this paper, we propose two similarity based mechanisms; WDES, to extract desired SERPs and store them in the local depository for offline browsing and WDICS, to integrate the requested contents and enable the user to perform the intended analysis and extract the desired information. Our experimental results show that WDES and WDICS outperform DEPTA (1) in terms of Precision and Recall.
Measurement of ladle slag oxygen activity using electrochemical sensor

Abstract The oxygen activity of the ladle slag may be measured in situ with an electrochemical sensor. The measurement principle of this sensor needs further clarification. An experimental and computational study has been carried out of the contribution of specific components to the oxygen activity of the slag and of the factors that influence oxygen activity measurement with the sensor. Experiments on an industrial and on a laboratory scale show that FeOx, SiO2 and MnO exert a measurable influence on the results. The measurements also show a marked influence of the dissolved oxygen content in the steel. The oxygen activity of the slags has been calculated thermodynamically and compared with the sensor measurements. A systematic difference is observed. A hypothesis on the working principle of the sensor and on the cause of occasional problematic measurement values is proposed.
Lipopolysaccharide-Induced Nitric Oxide, Prostaglandin E2, and Cytokine Production of Mouse and Human Macrophages Are Suppressed by Pheophytin-b

Sepsis is an overwhelming systemic response to infection that frequently results in tissue damage, organ failure, and even death. Nitric oxide (NO), prostaglandin E2 (PGE2), and cytokine overproduction are thought to be associated with the immunostimulatory cascade in sepsis. In the present study, we analyzed the anti-inflammatory efficacy of the pheophytin-b on both RAW 264.7 murine macrophage and purified human CD14+ monocytes stimulated with lipopolysaccharide (LPS) and elucidated the mechanisms by analyzing the cell signaling pathways known to be activated in sepsis. Pheophytin-b suppressed the overexpression of NO, PGE2, and cytokines in LPS-stimulated macrophages without inducing cytotoxicity. It also reduced NOS2 and COX-2 mRNA and protein levels. The inhibitory effects on NO, PGE2, and cytokine overproduction arose from the suppression of STAT-1 and PI3K/Akt pathways; no changes in NF-κB, MAPK, and AP-1 signaling were detected. Thus, pheophytin-b may represent a potential candidate to beneficially modulate the inflammatory response in sepsis.
Borrelia miyamotoi–Associated Neuroborreliosis in Immunocompromised Person

Borrelia miyamotoi is a newly recognized human pathogen in the relapsing fever group of spirochetes. We investigated a case of B. miyamotoi infection of the central nervous system resembling B. burgdorferi–induced Lyme neuroborreliosis and determined that this emergent agent of central nervous system infection can be diagnosed with existing methods.
Use of pre-conscious vision and geometric characterizations for automatic man-made object recognition

With the advent of commercial satellite sensors producing images with resolutions better than 5 m. , it is now possible to recognize man-made objects which were not visible at lower resolutions. In this paper we extend the work presented by Inglada and Giros (2004) to the use of high-level geometric descriptions and pre-conscious vision.
SVM feature selection and sample regression for Chinese medicine research

In this paper, SVM based feature selection methods are introduced for regression problem of COX2 inhibitor activity prediction in Chinese medicine quantitative structure-activity relationship (QSAR) research. We develop a recursive SVM feature selection algorithm for regression and compare its performance with genetic algorithm and SVM recursive feature elimination (SVM-RFE) algorithm. Experiments on real Chinese medicine dataset show that our method is a fast and accurate algorithm for Chinese medicine regression problem with a small number of samples.
Electrolytic synthesis of aqueous aluminum nanoclusters and in situ characterization by femtosecond Raman spectroscopy and computations

Significance The aqueous chemistry of Al has a large impact across the biosphere, hydrosphere, geosphere, and anthrosphere. Despite a century of study, aqueous Al chemistry and speciation are still not well understood because of the challenges of selectively isolating and synthesizing specific Al-containing aqueous clusters and of precisely characterizing those clusters. We report the atom- and step-economical electrolytic synthesis of aqueous Al clusters combined with improved femtosecond Raman spectroscopy and computations to elucidate the structures and formation pathways of aqueous clusters in situ. We demonstrate the unique power of this integrated platform by synthesizing and characterizing flat [Al13(μ3-OH)6(μ2-OH)18(H2O)24]15+ clusters in water, which are versatile precursors for large-scale preparation of Al2O3 thin films and nanoparticles for electronics, catalysis, and corrosion prevention. The selective synthesis and in situ characterization of aqueous Al-containing clusters is a long-standing challenge. We report a newly developed integrated platform that combines (i) a selective, atom-economical, step-economical, scalable synthesis of Al-containing nanoclusters in water via precision electrolysis with strict pH control and (ii) an improved femtosecond stimulated Raman spectroscopic method covering a broad spectral range of ca. 350–1,400 cm−1 with high sensitivity, aided by ab initio computations, to elucidate Al aqueous cluster structures and formation mechanisms in real time. Using this platform, a unique view of flat [Al13(μ3-OH)6(μ2-OH)18(H2O)24](NO3)15 nanocluster formation is observed in water, in which three distinct reaction stages are identified. The initial stage involves the formation of an [Al7(μ3-OH)6(μ2-OH)6(H2O)12]9+ cluster core as an important intermediate toward the flat Al13 aqueous cluster.
Cause of cerebral infarction in the carotid territory. Its relation to the size and the location of the infarct and to the underlying vascular lesion.

Seventy-three patients with acute nonhemorrhagic stroke in the carotid territory were investigated for the cause of the stroke: middle cerebral artery (MCA) occlusion/stenosis or internal carotid artery (ICA) occlusion/stenosis; embolus from the heart and extra-cranial arteries or thrombosis. The study is prospective and consecutive comprising stroke patients below the age of 75 years, admitted in the acute state i.e. within 3 days after stroke onset. Excluded were patients with intracerebral hematoma, subarachnoid hemorrhage, vertebrobasilar stroke and patients in whom another severe disease was present. Cerebral angiography and CT-scan were performed in all patients within one and two days after admission. CT-scan was repeated 2 weeks and 6 months later. Forty percent had MCA occlusion, none had MCA stenosis, 12% had ICA occlusion, 14% had severe ICA stenosis (half of these were associated with MCA occlusion) and 41% were without significant MCA/ICA lesions. Twenty-seven percent had large infarcts with a diameter greater than 3 cm; 34% had medium-sized infarcts with a diameter between 3 and 1.5 cm; 21% had small infarcts with a diameter less than 1.5 cm; 18% had no identifiable infarct on CT-scan. MCA occlusion was responsible for 62% of the large or medium-sized infarcts. ICA occlusion or severe ICA stenosis were responsible for only 27% of the large or medium-sized infarcts. Only 11% of the patients with small or no infarct on CT-scan had significant MCA/ICA lesion. (ABSTRACT TRUNCATED AT 250 WORDS)
TROTT Computer Program for Two-Dimensional Stress Wave Propagation

Abstract : TROTT is a Lagrangian finite-difference computer program for calculating two-dimensional stress wave propagation through solid, porous, and composite materials. The stress waves may be caused by impact, detonation of an explosive, or a prescribed velocity. The calculational procedure is the standard leapfrog method of von Neumann and Richtmyer, using artificial viscosity to smooth shock fronts. Quadrilateral or triangular cells are used. The momentum relations are derived by treating the cells as finite elements. Axisymmetric or planar flow can be handled. The constitutive relations include the standard Mie- Gruneisen equation-of-state and elastic-plastic, work-hardening deviator stress relations. A polytropic gas and detonating flow relations are provided for explosives. Ductile and brittle fracture and shear banding are provided by nucleation and growth models. Porous materials can be represented by a cap plasticity model. A model for layered composites is also present. The code is constructed for easy insertion of additional material models. The number of extra variables required for each cell for a material model can be specified on an input card. This manual includes many sample problems, a derivation of the flow equations, and a discussion of material models.
Ubiquitin Ser65 phosphorylation affects ubiquitin structure, chain assembly and hydrolysis

The protein kinase PINK1 was recently shown to phosphorylate ubiquitin (Ub) on Ser65, and phosphoUb activates the E3 ligase Parkin allosterically. Here, we show that PINK1 can phosphorylate every Ub in Ub chains. Moreover, Ser65 phosphorylation alters Ub structure, generating two conformations in solution. A crystal structure of the major conformation resembles Ub but has altered surface properties. NMR reveals a second phosphoUb conformation in which β5‐strand slippage retracts the C‐terminal tail by two residues into the Ub core. We further show that phosphoUb has no effect on E1‐mediated E2 charging but can affect discharging of E2 enzymes to form polyUb chains. Notably, UBE2R1‐ (CDC34), UBE2N/UBE2V1‐ (UBC13/UEV1A), TRAF6‐ and HOIP‐mediated chain assembly is inhibited by phosphoUb. While Lys63‐linked poly‐phosphoUb is recognized by the TAB2 NZF Ub binding domain (UBD), 10 out of 12 deubiquitinases (DUBs), including USP8, USP15 and USP30, are impaired in hydrolyzing phosphoUb chains. Hence, Ub phosphorylation has repercussions for ubiquitination and deubiquitination cascades beyond Parkin activation and may provide an independent layer of regulation in the Ub system.
Research on Credit Evaluation Model and Algorithm for B2B e-Commerce

Credit has been considered as one of the most important problems in e-commerce. There is less research on B2B e-commerce credit evaluation model and algorithm than C2C or B2C. A new enterprise credit evaluation model and algorithm for B2B e-commerce based on intermediate Web site is proposed. It is assumed that an enterprise's credit in the B2B e-commerce environment is composed of basic credit and transaction credit, and detailed transaction data are available and can be accessed for credit evaluation purpose. According to the BP neural network principles, the models with 3 layers are established to evaluate quantitative-indicators-based credit. Compared with basic credit, an enterprise's transaction credit is more practical for its potential trading partners on intermediate B2B website. Experimental results demonstrate the effectiveness of the new credit evaluation model and algorithm.
Chemical Degradation of RDX on Strongly Basic Ion-Exchange Resins,

Abstract : Chemical interaction of RDX on strongly basic ion-exchange resins has been investigated as a method for (1) removal and (2) disposal of RDX from water in a single step. The resin has been evaluated on both laboratory and pilot scales and shows no loss of efficiency after eight regeneration cycles. One cubic foot of resin was found capable of degrading and removing 99% of the RDX contained in 1300 gallons of tap water before regeneration was required. (Author)
Declarative platform for data sourcing games

Harnessing a crowd of users for the collection of mass data (data sourcing) has recently become a wide-spread practice. One effective technique is based on games as a tool that attracts the crowd to contribute useful facts. We focus here on the data management layer of such games, and observe that the development of this layer involves challenges such as dealing with probabilistic data, combined with recursive manipulation of this data. These challenges are difficult to address using current declarative data management framework works, and we thus propose here a novel such framework, and demonstrate its usefulness in expressing different aspects in the data management of Trivia-like games. We have implemented a system prototype with our novel data management framework at its core, and we highlight key issues in the system design, as well as our experimentations that indicate the usefulness and scalability of the approach.
On optimal importance sampling for discrete-time Markov chains

Importance sampling is a variance reduction technique for efficient simulation via a change of measure. In particular, it can be applied to rare event simulation of Markov chains. An optimal change of measure yielding a zero variance estimator always exists, but it explicitly depends on the unknown quantity of interest. Thus, it is typically neither known in advance nor available in simulations. In this paper, we investigate the form of optimal importance sampling for estimating state probabilities in discrete-time Markov chains, both over finite horizon and in steady state. We derive the optimal change of measure by utilizing only a general property, without using a priori knowledge of the quantity of interest. Our results show that optima! importance sampling for Markov chains cannot be performed by simulating an alternative Markov chain, since transition probabilities in each step must depend on the history of the already simulated process. This particularly indicates that combined dynamic/adaptive techniques should be applied, and that some traditional approaches are not really promising, which holds not only for Markov chains but also for higher level models such as Petri nets and Markovian queueing models.
Evolutionary layout: preserving the mental map during the development of class models

It is vital for any developer to keep track of changes during his project. Thus, it is common practice to take static snapshots of single class diagrams. But to preserve the mental map, the layout of a class diagrams sequence is necessary.Therefore, we present in this paper requirements to layout a sequence of class diagrams and an approach for a layout algorithm to fulfill them. Our main idea was to see a sequence of class diagrams as the evolution of one graph over time. We expressed the graph's evolution via a graph transformations sequence and enriched this with the concept of node aging. We extended also the well-known spring-embedder layout algorithm to layout single graphs from this new sequence with the concept of layout pattern to integrate a-priori-knowledge. The resulting algorithm has been integrated into the AGG-Tool, an environment for Attributed Graph Grammars, and produced good results on various class diagrams and general graph grammars.
Assessing the Feasibility of Monitoring Strain in Historical Tapestries Using Digital Image Correlation

Abstract: Digital image correlation (DIC) is used to monitor strain in a representative textile material and an historic tapestry. The validity of a ‘map function’ that allows 3D DIC displacement measurements to be obtained when the reference data are collected with a camera set‐up different from that of the deformed data is assessed. An experiment was devised to study the effects of DIC processing parameters (interrogation cell size and overlap) on strain measurements, and to investigate if the textile contains adequate contrast for DIC to operate. The study shows that the textile’s weave pattern can be used as the device for correlation. Long‐term tests for monitoring creep strain using DIC both in the laboratory and in situ are presented. The results show good correspondence between strain changes in the tapestry and relative humidity.
An Automatic Phase-Change Detection Technique for Colloidal Hard Sphere Suspensions

Colloidal suspensions of monodisperse spheres are used as physical models of thermodynamic phase transitions and as precursors to photonic band gap materials. However, current image analysis techniques are not able to distinguish between densely packed phases within conventional microscope images, which are mainly characterized by degrees of randomness or order with similar grayscale value properties. Current techniques for identifying the phase boundaries involve manually identifying the phase transitions, which is very tedious and time consuming. We have developed an intelligent machine vision technique that automatically identifies colloidal phase boundaries. The algorithm utilizes intelligent image processing techniques that accurately identify and track phase changes vertically or horizontally for a sequence of colloidal hard sphere suspension images. This technique is readily adaptable to any imaging application where regions of interest are distinguished from the background by differing patterns of motion over time.
Camera tamper detection using wavelet analysis for video surveillance

It is generally accepted that video surveillance system operators lose their concentration after a short period of time and may miss important events taking place. In addition, many surveillance systems are frequently left unattended. Because of these reasons, automated analysis of the live video feed and automatic detection of suspicious activity have recently gained importance. To prevent capture of their images, criminals resort to several techniques such as deliberately obscuring the camera view, covering the lens with a foreign object, spraying or de-focusing the camera lens. In this paper, we propose some computationally efficient wavelet domain methods for rapid camera tamper detection and identify some real-life problems and propose solutions to these.