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Epidermal growth factor receptors (EGFRs) are expressed on the ocular surface and play an important role in the maintenance of the corneal and conjunctival epithelium. Non-small cell lung cancer has been associated with abnormalities in the expression of this receptor, which led to targeted therapy for these patients. 1 EGFR inhibitors, including erlotinib and gefitinib, target the tyrosine kinase enzyme and have been shown to confer a 6.4% overall survival in patients with stage IIIB and IV nonsmall cell lung cancer. 2 The most common side effects of the EGFR inhibitor erlotinib include rash, diarrhea, anorexia, fatigue, nausea, and vomiting. 1,3 Ocular side effects develop in 17.8% of patients and include dry eye, trichomegaly, ectropion, keratitis, corneal ulceration, and perforation. 3 This case report illustrates a form of corneal toxicity secondary to a systemic EGFR inhibitor.

Iron ore tailings (IOT) are waste produced during mining of iron from its ore. Thus sustainable handling of iron ore tailings is of prime concern to all stakeholders who are into iron ore mining. Bottom ash is the waste material, which drops into the bottom of the furnace in latest large thermal power plants. The consumption and demand of construction materials has resulted in the extraction of sand from rivers. The extraction of sand is having adverse effects on rivers, causing degradation of rivers. Hence, in this thesis the effectiveness of iron ore tailings and bottom ash as fine aggregates in concrete is taken for study. Initially replacement of fine aggregate with 10%, 20%, 30%, 40% and 50% iron ore tailings was done. Then replacement of fine aggregate with 10%, 20%, 30%, 40% and 50% bottom ash was also done. The fresh and hardened state properties of concrete in both cases were studied and compared. The various tests have done include slump test, compacting factor test, compressive strength test, split tensile strength test and flexural strength test.

This paper presents a dynamic analysis of the free and forced vibration of a free-standing bridge of superelastic shape memory alloy TiNiCuCo film with ultra-low fatigue properties and evaluates its versatility for novel miniature scale damping applications. A thermodynamics-based finite element model is used to simulate the evolution of martensite phase fraction during load-induced martensitic phase transformation. The effects of pre-strain, strain rate and excitation load on the hysteresis of stress-strain characteristics are investigated in order to assess damping energies. The analysis is performed under non-isothermal conditions taking into account heat transfer and rate-dependence of release and absorption of latent heat. We show that damping energy can be maximized by applying an optimum pre-strain. A maximum damping capacity of 0.17 is determined for the case of complete stressstrain hysteresis loop during phase transformation.

The paper deals with the application of the artificial bee colony (ABC) method for hysteresis parameters identification. For the first time, the ABC method will be applied on hysteresis model optimization. For this purpose, two hysteresis models are tested: the first is based on a physical magnetic material behavior, which is Jiles-Atherton and the second is simpler, Fröhlich hysteresis model built on mathematical considerations. This method's robustness will be assessed, by comparing the experimental signals to model results. I. INTRODUCTION Electrical engines and electromagnetic machines are designed according to the customer requests and safety norms. Furthermore, the advanced technologies have to target the optimized operating conditions. For this purpose, it is necessary to build robust numerical modeling based on the magnetic material behavior. In literature, several models have been proposed and studied in large material application. It can be splitted into families: analytical ones: such as Rayleigh [1], Potter [2] or Fröhlich [3][4][5], which offer comfortable implementation in finite element code, but still limited to low or high magnetization behavior description. The second family is based on physical considerations such as the Preisach model [6] and the Jiles-Atherton model [7]. These are considered as the most robust and reliable models can be applied on soft and hard magnetic materials by parameter identification process. This task remains complex due to the inter dependency of each parameter to the other. The first investigation realized in this topic is based on iterative procedure [8]. It leads to good approximation of parameter's values but often presents convergence problems and can engender numerical instability. Other authors have proposed deterministic optimization methods [9][10], where the results were successful but request a great time calculation. Since two decades, stochastic optimization methods like generic algorithms and neural network [11][12][13] have been investigated. Other works combined between generic algorithms and simulated annealing [14]. It results accurate solution in a very short time. Recently, swarm intelligence method is used in electromagnetic applications. The most famous one is the particle swarm optimization (PSO) [15], inspired by the collective behavior of birds and fishes. Many experts have investigated this method