Optical imaging of retina in response to grating stimuli in cats

We examined the intrinsic signals in response to grating stimuli in order to determine whether the light-evoked intrinsic signals of the retina are due to changes in the photoreceptor activities induced by the image projected on to the retina or are due to neural activities of the inner retina. The retinas of the left eye of 12 cats under general anesthesia were examined by a functional imaging fundus camera. Near infrared light was used to monitor the reflectance changes (RCs) of the retina. Vertical grating were used to stimulate the retina at 4 Hz. The spatial frequencies of the gratings were 0.05, 0.11, 0.22, 0.43, 0.86, 1.73, and 3.46 cycles/degree (cpd). Ten images were averaged and used to analyze the RCs to obtain the peak value (PV) of a two dimensional fast Fourier transfer of the RCs. The wavefront aberrations (WA) were measured with a compact wavefront aberrometer and the spatial modulation transfer function (MTF) of the eye was calculated. The retinal reflectance image had a grating pattern. The PV of the spatial sensitivity curve was highest at low spatial frequencies (0.05 and 0.11 cpd), and the sensitivity decreased steeply with an increase in the spatial frequency. RCs were not detectable at 3.46 cpd. The MTF decreased gradually with increases in the spatial frequencies and was 0.68 at 3.46 cpd. The reflectance pattern of the retinal intrinsic signal elicited by grating stimuli of different spatial frequencies was different from that of the MTF. This suggests that the intrinsic signal represents not only the response of the photoreceptors but also other neuronal or vascular changes in the retina.

Does anticholinergics drug burden relate to global neuro-disability outcome measures and length of hospital stay?

Primary objective: To assess the relationship between disability, length of stay (LOS) and anticholinergic burden (ACB) with people following acquired brain or spinal cord injury. Research design: A retrospective case note review assessed total rehabilitation unit admission. Methods and procedures: Assessment of 52 consecutive patients with acquired brain/spinal injury and neuropathy in an in-patient neuro-rehabilitation unit of a UK university hospital. Data analysed included: Northwick Park Dependency Score (NPDS), Rehabilitation complexity Scale (RCS), Functional Independence Measure and Functional Assessment Measure FIM-FAM (UK version 2.2), LOS and ACB. Outcome was different in RCS, NPDS and FIM-FAM between admission and discharge. Main outcomes and results: A positive change was reported in ACB results in a positive change in NPDS, with no significant effect on FIM-FAM, either Motor or Cognitive, or on the RCS. Change in ACB correlated to the length of hospital stay (regression correlation = −6.64; SE = 3.89). There was a significant harmful impact of increase in ACB score during hospital stay, from low to high ACB on NPDS (OR = 9.65; 95% CI = 1.36–68.64) and FIM-FAM Total scores (OR = 0.03; 95% CI = 0.002–0.35). Conclusions: There was a statistically significant correlation of ACB and neuro-disability measures and LOS amongst this patient cohort.

Matching theory based travel plan aware charging algorithms in V2G smart grid networks

The frequency, time and places of charging have large impact on the Quality of Experience (QoE) of EV drivers. It is critical to design effective EV charging scheduling system to improve the QoE of EV drivers. In order to improve EV charging QoE and utilization of CSs, we develop an innovative travel plan aware charging scheduling scheme for moving EVs to be charged at Charging Stations (CS). In the design of the proposed charging scheduling scheme for moving EVs, the travel routes of EVs and the utility of CSs are taken into consideration. The assignment of EVs to CSs is modeled as a two-sided many-to-one matching game with the objective of maximizing the system utility which reflects the satisfactory degrees of EVs and the profits of CSs. A Stable Matching Algorithm (SMA) is proposed to seek stable matching between charging EVs and CSs. Furthermore, an improved Learning based On-LiNe scheduling Algorithm (LONA) is proposed to be executed by each CS in a distributed manner. The performance gain of the average system utility by the SMA is up to 38.2% comparing to the Random Charging Scheduling (RCS) algorithm, and 4.67% comparing to Only utility of Electric Vehicle Concerned (OEVC) scheme. The effectiveness of the proposed SMA and LONA is also demonstrated by simulations in terms of the satisfactory ratio of charging EVs and the the convergence speed of iteration.