Cobalamin, commonly known as vitamin B12, is a crucial micronutrient synthesized predominantly by a few microorganisms. In the human body, Vitamin B12 (Cobalamin) is essential for DNA synthesis and is required as a cofactor for functioning two crucial enzymes, methylmalonyl-CoA mutase and methionine synthase. The deficiency in these cobalamin-derivated coenzymes leads to enzyme activity dysfunction and an accumulation of their respective substrates, methylmalonic acid, and homocysteine,harming the brain and many other organs. Furthermore, deficiency in this micronutrient can lead to a wide spectrum of hematologic and neuropsychiatric disorders. In addition to vitamin B12 deficiency, some genetic disorders block the intracellular processing of Cobalamin to its cofactors and lead to symptoms somewhat similar to vitamin B12 deficiency. These disorders are called Cobalamin metabolism disorders. Many of them are reversible when diagnosed early and treated promptly. This group’s most common and well-understood disease is Cobalamin C (CblC) metabolism disorder. This case SERIES report aimed to provide a comprehensive overview of diverse clinical presentations within the spectrum of CblC metabolism disorder and the introduction of two cases of late-onset presentation with ataxia and repeated seizures as the first manifestation of the disorder. Few case reports are available, specifically in children, describing cerebellar ataxia and seizure as the first manifestations of late-onset CblC metabolism disorder. Additionally, this report sought to contribute to the existing literature by highlighting potential areas for timely recognition and targeted clinical and therapeutic interventions, thereby enhancing the comprehensive care and support for individuals affected by CblC metabolism disorder.

Time is one of the most difficult subjects in philosophy. Some philosophers believe that time is a reality and others assume it as an illusion. McTaggart has denied the reality of time. His argument is very famous in the philosophy of time and thus the recent discussions about time are affected by his argument.Events and moments، he thinks، can occur in time in two forms and thus there are two SERIES of time: 1) A SERIES in which two events and moments are ordered as past، present and future, 2) B SERIES in which the events and moments are ordered as a priori and a posterior. The A SERIES is necessary for time because without A SERIES time does not exist. At the same time، A SERIES leads to contradiction and time cannot exist as a real thing. Only one real and non-temporal SERIES، he believes، exists but it appears as time SERIES to us by our perception.

In recent years, nonlinear circuit analysis techniques have been extensively investigated. One of the most important reasons is the application development of solid-state devices at microwave frequencies. Different methods have been used to analysis large signal behavior of these devices. In this paper load-pull curves (one of design requirement) are obtained using Volterra SERIES. The main advantage of this technique is shortening the time of computations for weak nonlinear analysis in cases such as Class A power amplifiers. The proposed procedure has been coded in MATLAB. Using iterative methods, loads with constant output power have been obtained. Finally the results are compared to experimentally measured values and a fair degree of calculation between them is observed.

There are many studies discussing the correlation between air pollution and human health hazards. Yet, in Tehran there is not a survey using time SERIES methodology. Thus, we conducted a study based on time SERIES data on the topic in Tehran, Iran. Mean levels of NO, NO2, NOX, CO, 03, SO2 and PM10 (particulate matters smaller than 10micrometer in diameter) were measured in one station of Tehran's Air Quality Control Corporation and were used as main independent variables. Mean temperature, mean humidity, day of the week, month and season were considered as potential confounders and deaths in people older than 64 years in Tehran was the dependent variable. All the variables were measured during Mar. 1998 to Dec. 1999. Concentrations of air pollutants were different between seasons and so were the means of daily deaths. Out of main independent variables, SO2, CO and PM10 showed statistically significant relations with the dependent variable (P<0.05). After controling for confounders, there was 3.4%, 2.6% and 3.36% increase in death rates, respectively, for each interquartile ascending (increase from 25th centile to 75th centile) in association to the mentioned pollutant centile concentration. No autocorrelation between residuals was observed (r= -0.059). The study showed that meteorological variables can confound the relation between air pollution and rate of deaths per day.  

In this study a model based on using artificial neural network (ANN) for modeling Between 13 CNMR chemical shifts and chemical structures of a SERIES of organic Compounds (C3-C9) are described. Graph theory for presenting data to ANN was used; for achieving best model of ANN several topologies and its parameters were examined. In all steps root mean square error (RMS) xhere calculated. Which in the optimized Model RMS< 0.002 was obtained. The produced model were used for prediction of chemical shifts of other compound.