Modeling Surface Deformations and Hinging Regions in Reinforced Concrete Bridge Columns

A high-resolution model of a bridge column was developed using the computer program ABAQUS and the accuracy of the model was evaluated for the displacement field and the rotations of a bridge system subjected to biaxial shake-table loading. The effect of simulation parameters (reinforcing bar slip within the joint and stiffness degradation of the concrete) was studied to determine the goodness-of-fit of the displacement and rotation fields recorded during the dynamic response. A Fourier Domain Error Index analyses showed that yield stress of the reinforcement and the boundary conditions of the column submodel were important parameters, and the damage and stiffness degradation parameters were not as important for the goodness-of-fit of the finite element model. The computed rotations at the plastic hinge regions near the beam caps had the best correlation

Preparation of cellulose nanofibers with hydrophobic surface characteristics.

The aim of this study was to develop cellulose nanofibers with hydrophobic surface characteristics using chemical modification. Kenaf fibers were modified using acetic anhydride and cellulose nanofibers were isolated from the acetylated kenaf using mechanical isolation methods. Fourier transform infrared spectroscopy (FTIR) indicated acetylation of the hydroxyl groups of cellulose. The study of the dispersion demonstrated that acetylated cellulose nanofibers formed stable, well-dispersed suspensions in both acetone and ethanol. The contact angle measurements showed that the surface characteristics of nanofibers were changed from hydrophilic to more hydrophobic when acetylated. The microscopy study showed that the acetylation caused a swelling of the kenaf fiber cell wall and that the diameters of isolated nanofibers were between 5 and 50 nm. X-ray analysis showed that the acetylation process reduced the crystallinity of the fibers, whereas mechanical isolation increased it. The method used provides a novel processing route for producing cellulose nanofibers with hydrophobic surfaces

Brain function assessment in different conscious states

Background: The study of brain functioning is a major challenge in neuroscience fields as human brain has a dynamic and ever changing information processing. Case is worsened with conditions where brain undergoes major changes in so-called different conscious states. Even though the exact definition of consciousness is a hard one, there are certain conditions where the descriptions have reached a consensus. The sleep and the anesthesia are different conditions which are separable from each other and also from wakefulness. The aim of our group has been to tackle the issue of brain functioning with setting up similar research conditions for these three conscious states.Methods: In order to achieve this goal we have designed an auditory stimulation battery with changing conditions to be recorded during a 40 channel EEG polygraph (Nuamps) session. The stimuli (modified mismatch, auditory evoked etc.) have been administered both in the operation room and the sleep lab via Embedded Interactive Stimulus Unit which was developed in our lab. The overall study has provided some results for three domains of consciousness. In order to be able to monitor the changes we have incorporated Bispectral Index Monitoring to both sleep and anesthesia conditions.Results: The first stage results have provided a basic understanding in these altered states such that auditory stimuli have been successfully processed in both light and deep sleep stages. The anesthesia provides a sudden change in brain responsiveness; therefore a dosage dependent anesthetic administration has proved to be useful. The auditory processing was exemplified targeting N1 wave, with a thorough analysis from spectrogram to sLORETA. The frequency components were observed to be shifting throughout the stages. The propofol administration and the deeper sleep stages both resulted in the decreasing of N1 component. The sLORETA revealed similar activity at BA7 in sleep (BIS 70) and target propofol concentration of 1.2 μg/mL.Conclusions: The current study utilized similar stimulation and recording system and incorporated BIS dependent values to validate a common approach to sleep and anesthesia. Accordingly the brain has a complex behavior pattern, dynamically changing its responsiveness in accordance with stimulations and states. © 2010 Ozgoren et al; licensee BioMed Central Ltd

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%

Italian guidelines for primary headaches: 2012 revised version

The first edition of the Italian diagnostic and therapeutic guidelines for primary headaches in adults was published in J Headache Pain 2(Suppl. 1):105–190 (2001). Ten years later, the guideline committee of the Italian Society for the Study of Headaches (SISC) decided it was time to update therapeutic guidelines. A literature search was carried out on Medline database, and all articles on primary headache treatments in English, German, French and Italian published from February 2001 to December 2011 were taken into account. Only randomized controlled trials (RCT) and meta-analyses were analysed for each drug. If RCT were lacking, open studies and case series were also examined. According to the previous edition, four levels of recommendation were defined on the basis of levels of evidence, scientific strength of evidence and clinical effectiveness. Recommendations for symptomatic and prophylactic treatment of migraine and cluster headache were therefore revised with respect to previous 2001 guidelines and a section was dedicated to non-pharmacological treatment. This article reports a summary of the revised version published in extenso in an Italian version