The purpose of this paper is to analyze Iran's role in the global value chain (GVC) using data from the 2016 Inter-country Input-Output  (ICIO) tables. By examining Iran's forward and backward GVC participation indicators, the study aims to provide insights into the country's level of integration within international production networks. This paper adopts a Borin and Mancini (2023) approach, utilizing the ICIO tables to calculate Iran's forward and backward GVC participation indicators. These indicators serve as proxies for assessing Iran's involvement in producing inputs for re-export and using imported inputs for export-oriented production, respectively. The methodology involves rigorous data analysis and interpretation to derive meaningful insights. The findings of this study reveal that Iran plays a negligible role in the global value chain. Both forward and backward GVC participation indicators indicate limited integration with international production networks. This suggests a relatively isolated position for Iran in terms of GVC activities, highlighting potential challenges and opportunities for the country's economic development. This paper contributes to the literature by providing a comprehensive analysis of Iran's position in the global value chain using the latest available data. By focusing on forward and backward GVC participation indicators, the study offers novel insights into Iran's level of integration within international production networks. The findings have implications for policymakers, researchers, and practitioners interested in understanding Iran's economic dynamics and identifying strategies for enhancing its participation in the global economy.

This paper offers a modified circuit for improving linearization of power amplifier with based on the model of the Feed Forward circuit amplifier. With the help of mathematical model for the single power amplifier, the circuit is simulated und a demonstrator is built and measured. it is used a complex Taylor series for modeling the power amplifier by the approximation of the amplitude transfer function and the level-dependence of the transmission-phase of the power amplifier and can be understood as a simplified form of Volterra series. In our proof of concept experiment, we verified the concept but also found that the adjustment of the circuit is critically dependent on the drive conditions and linearization is achieved only for a narrow range of drive power. The simulation of the total circuit is largely determined by the models for the transmission characteristics of the two power amplifiers. The new circuit in compare with the conventional Feed Forward amplifier, in addition a significant increase in efficiency to minimize the power of the distortion signal 3IMD for large driving amplitude (large signals).

This paper presents a Transimpedance Amplifier (TIA) for high sensitivity Near Infrared Spectroscopy (NIRS). The proposed TIA is based on the Regulated Cascode (RGC) structure with an extra transistor employed to implement additional feed-forward path and achieve higher gain values. The extra transistor senses a partially amplified input signal, available in the conventional circuit, and conveys an additional ac current into the load, which provides a higher gain. In addition, a bandwidth extension method is introduced using a capacitor and resistor, which can improve amplifier’s bandwidth by 40%. The proposed TIA is designed in 0.18µm CMOS technology and achieves a transimpedance gain of 101.9dB with a -3dB bandwidth of 91.2 MHz considering 2pF of photodiode capacitance at the TIA input. The input referred noise is 4.4pA/√Hz while dissipating 151µW power.

The rapid discoveries of X-rays by Roentgen, natural radioactivity by Becquerel and radium by Curies at the end of 19th century changed broadly the worlds of physics, biology and medicine. At the close of the 20th century, fundamental discoveries in biology at moecular level, often appear to overshadow this earlier work. However as more basic discoveries are made these separate scientific eras merged to contribute to the conquest of disease, specially cancer. The rapid advancements achieved during recent years, mainly due to revolutionary methodological improvements, have led to an unparalleled explosion of information. The exponential growth of data so impressive that the conceptual evaluation of the material has seemed almost an insignificant part of the scientific process. All these achievements have allowed researchers to ask new questions or to rephrase old ones. The result is a virtual avalanche of new formed knowledge.