Spatial Asymmetric Two dimensional Continuous Abelian Sandpile Model

We insert some asymmetries in the continuous Abelian sandpile models, such as directedness and ellipticity. We analyze probability distribution of different heights and also find the field theory corresponding to the models. Also we find the fields associated with some height variables.Comment: 14 Pages, 11 Figure

Seizure episodes detection via smart medical sensing system

Cyber-physical systems (CPS) consist of seamless network of sensors and actuators integrated with physical processes related to human activities. The CPS exploits sensors and actuators to monitor and control different physical process that can affect the computations of the devices. This paper presents the monitoring of physical activities exploiting wireless devices as sensors used in medical cyber-physical systems. Patients undergoing epileptic seizures experience involuntary body movements such as jerking, muscle twitching, falling, and convulsions. The proposed method exploits S-Band sensing used in medical CPS that leverage wireless devices such as omni-directional antenna at the transmitter side, four-beam patch antenna at the receiver side, RF signal generator and vector signal analyzer that perform signal conditioning by providing amplitude and raw phase data. The method uses wireless monitoring and recording system for measurement and classification of a clinical condition (epileptic seizures) versus normal daily routine activities. The data acquired that are perturbations of the radio signal is analyzed as amplitude, phase information, and statistical models. Extracting the statistical features, we leverage various machine learning algorithms such as support vector machine, random forest, and K-nearest neighbor that classify the data to differentiate patient’s various activities such as press-ups, walking, sitting, squatting, and seizure episodes. The performance parameters used in three machine learning algorithms are accuracy, precision, recall, Cohen’s Kappa coefficient, and F-measure. The values obtained using five performance parameters provide the accuracy of more than 90%

Glucokinase gene promoter -30G>A polymorphism: a cross-sectional association study with obesity, diabetes Mellitus, hyperlipidemia, hypertension and metabolic syndrome in an Iranian hospital

OBJECTIVE: A -30G>A single nucleotide polymorphism in the promoter region of the glucokinase gene has been previously associated with obesity, insulin resistance and diabetes. The present study aimed to evaluate the association of this polymorphism with obesity and its comorbidities in a population from Northeast Iran. METHODS: Five hundred and forty-two subjects aged 18 to 65 years were included in the study and divided into normal (BMI<25, n=220), overweight (25<BMI<30, n=135) and obese (BMI>30, n=187) groups. All subjects were genotyped for the -30G>A polymorphism using the polymerase chain reaction-restriction fragment length polymorphism technique. RESULTS: The genotypes and allele frequencies of the three groups did not differ significantly (p>0.05). When the study population was categorized according to diabetes mellitus, hyperlipidemia, hypertension and metabolic syndrome status, no significant difference in -30G>A genotypes and alleles was found between the subgroups with and without these disorders (p>0.05), apart from a significantly higher frequency of the G allele in the hyperlipidemic vs. non-hyperlipidemic subgroup (p<0.05). CONCLUSION: The findings of the present study do not support an association between the -30G>A polymorphism and high body mass index in the Iranian population