Innovation a modern model for estimating volume of money laundering

Money laundering or dirty money laundering refers to a process which attempts to demonstrate as legal the source of money obtained through illegal or illegitimate activities. Inflation and recession are among unavoidable consequences of money laundering and will eventually lead to spread of poverty in society. Therefore, recent years have witnessed a great tendency towards the assessment of this phenomenon and the application of different methods to estimate its quantity and volume alongside other similar variables in the socio-economic context. The aim of this article is to explain the ways of modeling of economic relations in addition to introducing a new method for assessment of the quantity of dirty money based on mathematical methods, without any particular presumption. This is while other methods, due to their nature, have a variety of different premises and this has indeed created many problems, including the likelihood of having remarkable errors. The present study applies a combination of Bhatta charya method and arithmetic methods which are based on Tikhonov's regularization strategy and inverse problem in order to introduce a new equation for assessment of the quantity of dirty money. Keywords: Corruption, Poverty, Money Laundering, Tikhonov Regularization Strategy, Inverse Proble

Indoor environment assessment of special wards of educational hospitals for the detection of fungal contamination sources: A multi-center study (2019-2021)

Background and Purpose: The hospital environment was reported as a real habitat for different microorganisms, especially mold fungi. On the other hand, these opportunistic fungi were considered hospital-acquired mold infections in patients with weak immune status. Therefore, this multi-center study aimed to evaluate 23 hospitals in 18 provinces of Iran for fungal contamination sources.Materials and Methods: In total, 43 opened Petri plates and 213 surface samples were collected throughout different wards of 23 hospitals. All collected samples were inoculated into Sabouraud Dextrose Agar containing Chloramphenicol (SC), and the plates were then incubated at 27-30ºC for 7-14 days.Results: A total of 210 fungal colonies from equipment (162, 77.1%) and air (48,22.9%) were identified. The most predominant isolated genus was Aspergillus (47.5%),followed by Rhizopus (14.2%), Mucor (11.7%), and Cladosporium (9.2%). Aspergillus(39.5%), Cladosporium (16.6%), as well as Penicillium and Sterile hyphae (10.4% each), were the most isolates from the air samples. Moreover, intensive care units (38.5%) and operating rooms (21.9%) had the highest number of isolated fungal colonies. Out of 256 collected samples from equipment and air, 163 (63.7%) were positive for fungal growth.The rate of fungal contamination in instrument and air samples was 128/213 (60.1%) and 35/43 (81.2%), respectively. Among the isolated species of Aspergillus, A. flavus complex (38/96, 39.6%), A. niger complex (31/96, 32.3%), and A. fumigatus complex (15/96, 15.6%) were the commonest species.Conclusion: According to our findings, in addition to air, equipment and instrument should be considered among the significant sources of fungal contamination in the indoor environment of hospitals. Airborne fungi, Hospital, Indoor air, Equipment, Sources of fungal contamination in the indoor environment of hospitals