Portfolio Optimization based on Synthetic Fish Congestion Algorithm and Artificial Intelligence: In the Condition of Uncertainty and Half-Variance Risk

The issue of stock portfolio optimization is the most well-known issue in the area of optimization. The purpose of this issue is to create a portfolio among different stocks in such a way that it has the highest returns and the least risk. The problem of optimal selection of stock portfolio is one of the Non-deterministic polynomial hardproblems (NP-hard). For this reason, this article introduces a new hybrid algorithm based on artificial immunity algorithm and swarm of fish algorithm. The computational results show that the proposed combination method has the ability to find the best investment boundary in comparison to other proposed methods.

İMMUNPROFILAKTIKANIN TƏŞKILININ ƏSASLARI, ONUN EFFEKTIVLIYININ VƏ TƏHLÜKƏSIZLIYININ QIYMƏTLƏNDIRILMƏSI

The purpose of this article is to investigate the growing number of viral diseases, to gather information on what measures should be taken against them and to educate the population. The immunological structure of the population is formed due to increased insensitivity to pathogenic microorganisms, which occurs through the formation of natural immunity (inherited or acquired as a result of an infectious process) and artificial immunity (created through immunoprophylaxis). The level of the immunological structure of the population affects the direction (trend) of the epidemic process. The higher the AID for a particular infectious disease, the lower the incidence, as well as the risk of group illnesses or outbreaks Key words: immunology, prophylaxis, natural immunity, artificial immunity, vaccination, vaccine, acquired immunity, serum, foreign antigen, organism, hereditary, physiological feature, anatomical feature

Predicting the artificial immunity induced by RUTI® vaccine against tuberculosis using universal immune system simulator (UISS)

Background Tuberculosis (TB) represents a worldwide cause of mortality (it infects one third of the world’s population) affecting mostly developing countries, including India, and recently also developed ones due to the increased mobility of the world population and the evolution of different new bacterial strains capable to provoke multi-drug resistance phenomena. Currently, antitubercular drugs are unable to eradicate subpopulations of Mycobacterium tuberculosis (MTB) bacilli and therapeutic vaccinations have been postulated to overcome some of the critical issues related to the increase of drug-resistant forms and the difficult clinical and public health management of tuberculosis patients. The Horizon 2020 EC funded project “In Silico Trial for Tuberculosis Vaccine Development” (STriTuVaD) to support the identification of new therapeutic interventions against tuberculosis through novel in silico modelling of human immune responses to disease and vaccines, thereby drastically reduce the cost of clinical trials in this critical sector of public healthcare. Results We present the application of the Universal Immune System Simulator (UISS) computational modeling infrastructure as a disease model for TB. The model is capable to simulate the main features and dynamics of the immune system activities i.e., the artificial immunity induced by RUTI® vaccine, a polyantigenic liposomal therapeutic vaccine made of fragments of Mycobacterium tuberculosis cells (FCMtb). Based on the available data coming from phase II Clinical Trial in subjects with latent tuberculosis infection treated with RUTI® and isoniazid, we generated simulation scenarios through validated data in order to tune UISS accordingly to STriTuVaD objectives. The first case simulates the establishment of MTB latent chronic infection with some typical granuloma formation; the second scenario deals with a reactivation phase during latent chronic infection; the third represents the latent chronic disease infection scenario during RUTI® vaccine administration. Conclusions The application of this computational modeling strategy helpfully contributes to simulate those mechanisms involved in the early stages and in the progression of tuberculosis infection and to predict how specific therapeutical strategies will act in this scenario. In view of these results, UISS owns the capacity to open the door for a prompt integration of in silico methods within the pipeline of clinical trials, supporting and guiding the testing of treatments in patients affected by tuberculosis.

Asymptotic Output Tracked Artificial Immunity Controller for Eco-Maximum Power Point Tracking of Wind Turbine Driven by Doubly Fed Induction Generator

This paper aims to design a controller for a Doubly Fed Induction Generator (DFIG) targeting the Eco-Maximum Power Point Tracking (EMPPT) for environmental aspects. The proposed controller consists of two clusters, which are the novel Artificial Immunity sensorless Eco-Maximum Power Point Tracking (AI EMPPT) and the asymptotic non-linear control techniques. The main target of the AI EMPPT is to reduce the carbon dioxide emission by generating the maximum possible power from the renewable electrical energy resource, which is wind electrical power generation to replace the fossil-fuel conventional generation. To build the AI EMPPT, an Artificial Immunity System Estimator (AISE) based on artificial immunity technique and a Model Reference Adaptive System (MRAS) are used to estimate the DFIG rotor speed. Then, the AI EMPPT is applied to provide the reference electromagnetic torque signal. Subsequently, the reference electromagnetic torque interacts with the estimated generator speed, determined by the wind mechanical power, to supply the wind electrical power. The second cluster is the asymptotic non-linear control technique which proposes the reference signal tracking of the rotor direct and quadratic current, respectively. Thus, assigning specific zeros through feedback ensures the reproduction of an output that converges asymptotically to a required reference rotor current. For online operation, the Artificial Immunity Technique (AIT) is utilized to deal with the generated control reference signal. A proposal hardware implementation on Field Programmed Gate Array (FPGA) is also presented. The introduced approach was applied to a wind turbine generator driving a 3.7 kW load. MATLAB program was used to simulate and test the performance of the proposed control methods. The results to show the effectiveness of the proposed technique. The reduction in CO2 emission was calculated.

Emilio Fernández, Gabriel Figueroa, and the Race for Mexico’s Body

This chapter looks at an especially interesting articulation of the posthuman within the indigenista films of Emilio “El Indio” Fernández. It identifies an attempt to modernize indigenous peasants by exposing their bodies to modern medicine. The chapter views these films in the context of Roberto Esposito’s “immunization paradigm,” a biopolitical theory that compares the medical process of immunization to the state’s role of subject creation. When a people lacks a natural immunity to a vice (improper performativity of race and gender in the case of these films), a new actor, such as the state, must step in and provide an artificial immunity. Using this theoretical framework, the chapter analyzes the films Río Escondido (1947), María Candelaria (1944), Enamorada (1946), and The Torch (1950). The readings suggest that we approach these films as allegories for a postrevolutionary society where immunological discourses prescribe appropriate gender and racial performativity for the nation.