A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price

Creating an intelligent system that can accurately predict stock price in a robust way has always been a subject of great interest for many investors and financial analysts. Predicting future trends of financial markets is more remarkable these days especially after the recent global financial crisis. So traders who access to a powerful engine for extracting helpful information throw raw data can meet the success. In this paper we propose a new intelligent model in a multi-agent framework called bat-neural network multi-agent system (BNNMAS) to predict stock price. The model performs in a four layer multi-agent framework to predict eight years of DAX stock price in quarterly periods. The capability of BNNMAS is evaluated by applying both on fundamental and technical DAX stock price data and comparing the outcomes with the results of other methods such as genetic algorithm neural network (GANN) and some standard models like generalized regression neural network (GRNN), etc. The model tested for predicting DAX stock price a period of time that global financial crisis was faced to economics. The results show that BNNMAS significantly performs accurate and reliable, so it can be considered as a suitable tool for predicting stock price specially in a long term periods.     

The Interplay of Modulus,Strength, and Ductility in Adhesive Design Using Biomimetic Polymer Chemistry

High‐performance adhesives require mechanical properties tuned to demands of the surroundings. A mismatch in stiffness between substrate and adhesive leads to stress concentrations and fracture when the bonding is subjected to mechanical load. Balancing material strength versus ductility, as well as considering the relationship between adhesive modulus and substrate modulus, creates stronger joints. However, a detailed understanding of how these properties interplay is lacking. Here, a biomimetic terpolymer is altered systematically to identify regions of optimal bonding. Mechanical properties of these terpolymers are tailored by controlling the amount of a methyl methacrylate stiff monomer versus a similar monomer containing flexible poly(ethylene glycol) chains. Dopamine methacrylamide, the cross‐linking monomer, is a catechol moiety analogous to 3,4‐dihydroxyphenylalanine, a key component in the adhesive proteins of marine mussels. Bulk adhesion of this family of terpolymers is tested on metal and plastic substrates. Incorporating higher amounts of poly(ethylene glycol) into the terpolymer introduces flexibility and ductility. By taking a systematic approach to polymer design, the region in which material strength and ductility are balanced in relation to the substrate modulus is found, thereby yielding the most robust joints.     

A novel temperature-tolerant foamed resin for enhanced oil recovery

The synthesis and performance of a novel temperature-tolerant foamed resin for enhanced oil recovery were investigated using various methods, including infrared, NMR, scanning electron microscopy (SEM), and displacement experiments. Polycondensation of furfuryl alcohol prepolymers was confirmed by the infrared and NMR results. The poor temperature tolerance of furfuryl alcohol prepolymers after gelation at high temperatures is mainly due to the fracture of furan rings. The addition of ester additives is an effective method of increasing the temperature tolerance of the prepared foamed resins and can effectively reduce the weight-loss rate of the polycondensation products. The SEM results show that the skeleton structure of the foamed resin remains intact after high-temperature treatment. Thus, the novel plugging agent system has excellent thermal stability and still has a high strength (>0.8 MPa) after high-temperature aging treatment for 40 days, giving the prepared foamed resin a good plugging performance (plugging rate > 91%) at 250 °C. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47161.     

The control of sea lice in Atlantic salmon by selective breeding

Sea lice threaten the welfare of farmed Atlantic salmon and the sustainability of fish farming across the world. Chemical treatments are the major method of control but drug resistance means that alternatives are urgently needed. Selective breeding can be a cheap and effective alternative. Here, we combine experimental trials and diagnostics to provide a practical protocol for quantifying resistance to sea lice. We then combined quantitative genetics with epidemiological modelling to make the first prediction of the response to selection, quantified in terms of reduced need for chemical treatments. We infected over 1400 young fish with Lepeophtheirus salmonis, the most important species in the Northern Hemisphere. Mechanisms of resistance were expressed early in infection. Consequently, the number of lice per fish and the ranking of families were very similar at 7 and 17 days post infection, providing a stable window for assessing susceptibility to infection. The heritability of lice numbers within this time window was moderately high at 0.3, confirming that selective breeding is viable. We combined an epidemiological model of sea lice infection and control on a salmon farm with genetic variation in susceptibility among individuals. We simulated 10 generations of selective breeding and examined the frequency of treatments needed to control infection. Our model predicted that substantially fewer chemical treatments are needed to control lice outbreaks in selected populations and chemical treatment could be unnecessary after 10 generations of selection. Selective breeding for sea lice resistance should reduce the impact of sea lice on fish health and thus substantially improve the sustainability of Atlantic salmon production.     

Global optimization for power dispatch problems based on theory of moments

Non-convex of an optimal power dispatch problem makes it difficult to guarantee the global optimum. This paper presents a convex relaxation approach, called the Moment Semidefinite Programming (MSDP) method, to facilitate the search for deterministic global optimal solutions. The method employs a sequence of moments, which can linearize polynomial functions and construct positive semidefinite moment matrices, to form an SDP convex relaxation for power dispatch problems. In particular, the rank of the moment matrix is used as a sufficient condition to ensure the global optimality. The same condition can also be leveraged to estimate the number of global optimal solution(s). This method is effectively applied to {0,1}-economic dispatch (ED) problems and optimal power flow (OPF) problems. Simulation results showed that the MSDP method is capable of solving {0,1}-ED problems with integer values directly, and is able to identify if more than one global optimal solutions exist. In additional, the method can obtain rank-1 moment matrices for OPF’s counterexamples of existing SDP method, this ensures the global solution and overcomes the problem that existing SDP method cannot meet the rank-1 condition sometimes.     

Design of an antibacterial gelatin based on a covalent protein–protein coupling

An antibacterial peptide (AMP), i.e., nisin, was covalently bound to gelatin through a protein–protein coupling. Various reaction conditions were tested to study and optimize parameters of grafting e.g., orientation and density of AMP, which could impact the final antibacterial activity of the modified biopolymer. Modification was investigated by Fourier transform infrared (FT‐IR) spectroscopy and zeta potential. The antibacterial activity of the nisin‐enriched gelatin was evaluated against two staphylococci bacterial strains, i.e., Staphylococus epidermidis and Staphylococcus aureus. A higher activity was found for gelatin modified at pH = 7.4 revealing an influence of the nisin orientation on the protein antibacterial property. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41825.     

Alloying behavior and novel properties of CoCrFeNiMn high-entropy alloy fabricated by mechanical alloying and spark plasma sintering

An equiatomic CoCrFeNiMn high-entropy alloy was synthesized by mechanical alloying (MA) and spark plasma sintering (SPS). During MA, a solid solution with refined microstructure of 10 nm which consists of a FCC phase and a BCC phase was formed. After SPS consolidation, only one FCC phase can be detected in the HEA bulks. The as-sintered bulks exhibit high compressive strength of 1987 MPa. An interesting magnetic transition associated with the structure coarsening and phase transformation was observed during SPS process.     

Nonlinear viscoelastic modeling of soft polymers

A one‐dimensional phenomenological constitutive model, representing the nonlinear viscoelastic behavior of polymers is developed in this study. The proposed model is based on a modification of the well‐known three element standard solid model. The linear dashpot is replaced by an Eyring type one, while the nonlinearity is enhanced by a nonlinear, strain dependent spring constant. The new constitutive model was proved to be capable of capturing the main aspects of nonlinear viscoelastic response, namely, monotonic and cyclic loading, creep and stress relaxation, with the same parameter values. Model validation was tested on the experimental results at various modes of deformation for two elastomeric type materials, performed elsewhere. A very good agreement between model simulations and experimental data was obtained in all cases. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42141.     

Detection of Multiple Blockages in Parallelized Microreactors

In a plant consisting of parallelized microreactors (MRs), the product quality is lowered because of a lack of flow uniformity among them when blockage occurs. It is not practical to install sensors in every MR from the viewpoint of cost when detecting the blocked MRs. In the previous study, the multiple blockage detection (MBD) method using a small number of sensors was proposed, but its performance became low when the number of sensors decreased. Here, the conventional algorithm for MBD is improved by considering the process behavior on blockage occurrence, and the effectiveness of the improved algorithm is demonstrated through a numerical case study. The effects of flow distributor types and sensor types on the MBD performance are numerically investigated.     

Simulation of thermal barrier coating spallation induced by the initiation/growth/coalescence of internal crack and interfacial crack based on a real image model

In the furnace cycle test, the growth of oxide film leads to the propagation and coalescence of multiple cracks near the interface, which should be responsible for the spallation of thermal barrier coatings (TBCs). A TBC model with real interface morphology is created, and the near-interface large pore is retained. The purpose of this work is to clarify the mechanism of TBC spallation caused by successive initiation, propagation, and linkage of cracks near the interface during thermal cycle. The dynamic growth of thermally grown oxide (TGO) is carried out by applying a stress-free strain. The crack nucleation and arbitrary path propagation in YSZ and TGO are simulated by the extended finite element method (XFEM). The debonding along the YSZ/TGO/BC interface is evaluated using a surface-based cohesive behavior. The large-scale pore in YSZ near the interface can initiate a new crack. The ceramic crack can propagate to the YSZ/TGO interface, which will accelerate the interfacial damage and debonding. For the TGO/BC interface, the normal compressive stress and small shear stress at the valley hinder the further crack propagation. The growth of YSZ crack and the formation of through-TGO crack are the main causes of TBC delamination. The accelerated BC oxidation increases the lateral growth strain of TGO, which will promote crack propagation and coalescence. The optimization design proposed in this work can provide another option for developing TBC with high durability.