Miniaturized atomic vapor cells are useful devices that would trace activity of electrical signals of ‎‎brain, Nitrogen vacancy center magnetometry, electric and magnetic fields' sensors and some other ‎applications. High ‎signal to noise ratio in these miniaturized systems is one of the main bottlenecks ‎which must be ‎managed by selective spectroscopy methods. Here we introduce novel type of atomic ‎vapor cell based on Rubidium hot atomic vapor suitable to ‎increase spatial resolution of ‎magnetometers and advantages of frequency modulation spectroscopy ‎method to increase spectral ‎resolution. These cells fabricate in 10-3 mbarr base pressure and under nitrogen Gas filling in clean ‎vacuum system. Combination of these cells and spectroscopy method would ‎be used in feedback ‎loops of laser system of atomic sensors to lock on desired atomic transition. ‎These ideas for new ‎miniaturized cell can open new insight in quantum based devices in new generation of quantum ‎sensor's, atomic clock or quantum computation applications.‎

Background: Speech perception ability depends on auditory and extra-auditory elements. The signal-to-noise ratio (SNR) is an extra-auditory element that has an effect on the ability to normally follow speech and maintain a conversation. Speech in noise perception difficulty is a common complaint of the elderly. In this study, the importance of SNR magnitude as an extra-auditory effect on speech perception in noise was examined in the elderly. Methods: The speech perception in noise test (SPIN) was conducted on 25 elderly participants who had bilateral low– mid frequency normal hearing thresholds at three SNRs in the presence of ipsilateral white noise. These participants were selected by available sampling method. Cognitive screening was done using the Persian Mini Mental State Examination (MMSE) test. Results: Independent T-test, ANNOVA and Pearson Correlation Index were used for statistical analysis. There was a significant difference in word discrimination scores at silence and at three SNRs in both ears (p≤ 0. 047). Moreover, there was a significant difference in word discrimination scores for paired SNRs (0 and +5, 0 and +10, and +5 and +10 (p≤ 0. 04)). No significant correlation was found between age and word recognition scores at silence and at three SNRs in both ears (p≥ 0. 386). Conclusion: Our results revealed that decreasing the signal level and increasing the competing noise considerably reduced the speech perception ability in normal hearing at low– mid thresholds in the elderly. These results support the critical role of SNRs for speech perception ability in the elderly. Furthermore, our results revealed that normal hearing elderly participants required compensatory strategies to maintain normal speech perception in challenging acoustic situations.

Purpose: Recruiting the Pharmacokinetic (PK) parameters estimated from non-invasive methods such as Dynamic Contrast Enhanced MRI (DCE-MRI) to evaluate or plan treatment procedure is widely investigated in clinical practices. Interpretation of the DCE-MRI data is highly dependent to precision and accuracy of the estimated parameters. One of the most effective factors on the DCE-MR images and on the contrast concentration profile is the Signal to Noise Ratio (SNR). This work focuses on the analytical evaluation of the noise effect on accuracy of the estimated PK parameters in DCE-MRI studies. Materials and Methods: Tofts model as a popular pharmacokinetic model and model selection technique was used to simulate 3470 time curves of contrast concentration. Maximum likelihood estimator as a minimum variance unbiased estimator was recruited to estimate the PK parameters. Eleven levels of signal to noise ratios (SNR= 5, 8, 10, 13, 15, 20, 25, 30, 35, 50, Noiseless) were added to the simulated CA concentration profiles. The PK parameters were estimated for 11 series data and then Mean Percentage Error (MPE) was calculated for estimated parameters. Results: The results indicate that the most sensitive parameter to the SNR of the DCE-MR images is inverse transfer constant. A SNR greater than 25 was found to ensure a reasonable error (MPE <5%) in all models parameters. Conclusion: Clinical decision based on the DCE-MRI data analysis and estimated PK parameters needs a good image quality (SNR>25), an accurate and robust estimator and correct pharmacokinetic model selection.

Background and Aim: The output Signal-to-Noise Ratio (SNR) is one of the essential factors in hearing aid benefits. There is limited evidence regarding SNR improvement by the Channel-Free (CFHA) and Multi-Channel Hearing Aid (MCHA) and the speech understanding in noise through them. This study aimed to investigate the extent to which output SNR was modified by CFHA and MCHA processing and the variation in aided speech recognition abilities with a change in output SNR. Methods: Thirty-six participants aged 50–65 years were included. A chosen CFHA and MCHA were used to obtain the output SNR and sentence recognition in noise in four different processing algorithms (linear, linear+noise reduction, WDRC, WDRC+noise reduction). Hagerman’s phase inversion technique was used to measure the attenuation of noise and, in turn, to obtain the output SNR of the hearing aid. Results: In all hearing aid processing algorithms among those with normal hearing and people with hearing loss, the output of CFHA revealed higher attenuation values than that of MCHA. There was a significant effect of the hearing aids and processing algorithms in both normal and individuals with hearing impairment on the mean SNR. Further, multiple linear regression analysis results showed that whether the hearing is channel-free or multichannel significantly predicted speech recognition scores, while output SNR and processing algorithms did not. Conclusion: The signal processing algorithms in CFHA had greater noise attenuation values, better output SNR, and speech recognition scores, showing an advantage over the modern MCHA among individuals with hearing impairment.