Half-Metallic Magnetism of Quaternary Heusler Compounds Co2Fe x Mn1−x Si(x =0,0.5, and 1.0): First-Principles Calculations

Using first-principles calculations, the structural, electronic, and magnetic properties of ferromagnetic half-metallic full-Heusler Co₂FeSi, Co₂MnSi and Co₂ Fe _0.5Mn _0.5Si alloy via the full-potential linearized augmented plane-wave (FP-LAPW) method in the generalized gradient (GGA) and GGA + U approximations are compared with other experimental and theoretical results. The electronic band structures and density of states (DOS) of the compounds indicate they are half metallic because of the existence of the energy gap in the minority spin (DOS and band structure), which yields perfect spin polarization. The half metallicity of the obtained material may prove useful for applications in spin-polarizers and spin-injectors of magnetic nanodevices. The calculated total spin magnetic moments are almost exactly that expected from the Slater-Pauling rule.     

Synthesis and antioxidant activities of some novel fluorinated spiro[oxindole-thiazolidine] fused with sulfur and phosphorus heterocycles

Facile routes were achieved for the synthesis of novel fluorinated spiro[oxindole-thiazolidinone] fused with some sulfur and phosphorus heterocycles starting from 5-fluoro-3^′-(4-fluorophenyl)-4^′H-spiro[indole-3,2^′-thiazolidine]-2,4^′(1H)-dione (1) via its reaction with trifluoroacetamide, 2-chloro-6-fluorobenzaldehyde and hydrazine hydrate followed by treatment with some suitable sulfur and phosphorus reagents. The antioxidant activities of the synthesized compounds were also evaluated.     

On-line monitoring of vacuum drying of theophylline using NIR spectroscopy: solid-state transitions,water content and semi-empirical modeling

The aim of this work was to monitor in-line and at a real time, the solid-state forms during pharmaceuticals manufacturing. It concerns the dehydration behavior and the solid-state transitions of theophylline in an agitated vacuum contact dryer. First, a near infrared spectroscopy (NIRS) method was performed using a reflectance diffuse probe to measure the in-line and in-situ exact composition of the mixture of different forms of theophylline and water content during drying. A multivariate modeling has been investigated to build a robust model which can predict four components at the same time during drying process. The XRPD analysis was used as a reference method in the process of calibration of NIRS. The indicators of the accuracy in quantitative spectral analysis confirm the robustness of the model and the efficiency of the method of calibration. Second, the kinetics of solid state transformations were investigated. It was shown that the dehydration advanced first by the formation of the metastable anhydrate and after a lag time of the stable one. Once the stable form appeared, formation of the metastable form came to an end. The temperature was found out to be the main factor controlling the overall process rate but also the final contents of the stable and metastable anhydrates for the considered dryer and operating conditions range. Finally, a semi-empirical drying model was proposed and significant quantitative differences were found, particularly at the product temperature which was probably caused by the excessive simplicity of the model.     

ADAGE: a framework for supporting user-driven ad-hoc data analysis processes

Data analysis is an important part of the scientific process carried out by domain experts in data-intensive science. Despite the availability of several software tools and systems, their use in combination with each other for conducting complex types of analyses is a very difficult task for non-IT experts. The main contribution of this paper is to introduce an open architectural framework based on service-oriented computing (SOC) principles called the Ad-hoc DAta Grid Environment (ADAGE) framework that can be used to guide the development of domain-specific problem-solving environments or systems to support data analysis activities. Through an application of the ADAGE framework and a prototype implementation that supports the analysis of financial news and market data, this paper demonstrates that systems developed based on the framework allow users to effectively express common analysis processes. This paper also outlines some limitations as well as avenues for future research.     

Generative adversarial network (GAN) and enhanced root mean square error (ERMSE): deep learning for stock price movement prediction

The prediction of stock price movement direction is significant in financial circles and academic. Stock price contains complex, incomplete, and fuzzy information which makes it an extremely difficult task to predict its development trend. Predicting and analysing financial data is a nonlinear, time-dependent problem. With rapid development in machine learning and deep learning, this task can be performed more effectively by a purposely designed network. This paper aims to improve prediction accuracy and minimizing forecasting error loss through deep learning architecture by using Generative Adversarial Networks. It was proposed a generic model consisting of Phase-space Reconstruction (PSR) method for reconstructing price series and Generative Adversarial Network (GAN) which is a combination of two neural networks which are Long Short-Term Memory (LSTM) as Generative model and Convolutional Neural Network (CNN) as Discriminative model for adversarial training to forecast the stock market. LSTM will generate new instances based on historical basic indicators information and then CNN will estimate whether the data is predicted by LSTM or is real. It was found that the Generative Adversarial Network (GAN) has performed well on the enhanced root mean square error to LSTM, as it was 4.35% more accurate in predicting the direction and reduced processing time and RMSE by 78 s and 0.029, respectively. This study provides a better result in the accuracy of the stock index. It seems that the proposed system concentrates on minimizing the root mean square error and processing time and improving the direction prediction accuracy, and provides a better result in the accuracy of the stock index.

     

Designing and Managing Human-AI Interactions

Information Systems Frontiers -     

Combined system for the simultaneous optical and electrochemical monitoring of intra- and extracellular NO produced by glioblastoma cells

A combined, optospectroscopic and electrochemical assay system for the simultaneous monitoring of intra- and extracellular production of biologically important species has been developed and assessed. The present model system evaluates intra- and extracellular nitric oxide produced by stimulated glioblastoma multiform cell line (A172). The production of endogenous NO was induced by phorbol-12-myristate-13-acetate and inhibited by N(omega)-nitro-l-arginine methyl ester. Intracellular production of NO was monitored via fluorescence image analysis using a 4,5-diaminofluorescein probe, while extracellular NO release was monitored via a chemically modified electrode, which was incorporated into an optically transparent cell chip. The results indicated that there was no mutual interference between the optical and electrochemical measurement systems. The response time of the combined optical/electrochemical system was found to be in the range of a few tens of seconds.     

Distribution of adhesive drops within fibre bundles

The motion of a drop along a fibre is studied to formulate a method by which adhesives could be distributed within fibre bundles. The drops had to be located at the cross-points of fibres to provide strength and flexibility to the mat. Among the various methods of application, described in detail, only the solution method gave satisfactory results. An empirical relationship was derived to estimate the mass of the adhesives retained by the fibres.     

Simultaneous interpenetrating polymer networks based on bromoacrylated castor oil polyurethane

In the first part of this study, simultaneous addition of bromine and acrylate to the double bonds of castor oil was achieved. In the second part of the study, bromoacrylated castor oil (BACO) was reacted with toluenediisocyanate (TDI), to form a prepolyurethane (BACOP). The prepolyurethanes were reacted with styrene (STY), 2‐hydroxyethyl methacrylate (HEMA), methyl methacrylate (MMA), and 3‐(acryloxy)‐2‐hydroxy propyl methacrylate (AHPMA) free radically, using the acrylate functional group to prepare the simultaneous interpenetrating polymer networks (SINs). 2,2′‐Azobis (isobutyronitrile) (AIBN) was used as the initiator and diethylene glycol dimethacrylate (DEGDMA) was used as the crosslinker. BACO and BACOP were characterized by IR, ¹H‐NMR, and ¹³C‐NMR techniques. Synthesized polymers were characterized by their resistance to chemical reagents, thermogravimetric analysis, and dynamic mechanical thermal analyzer (DMTA). All the polymers decomposed with 6–10% weight loss in a temperature range of 25–240°C. MMA‐type SIN showed the highest T_g (126°C), while STY‐type SINs showed the highest storage modulus (8.6 × 10⁹ Pa) at room temperature, with respect to other synthesized SINs. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 2947–2955, 2006