Tag: pubmed

Soc Work Public Health. 2022 Oct 15:1-11. doi: 10.1080/19371918.2022.2134249. Online ahead of print.

ABSTRACT

The purpose of this study was to examine the impact of socioeconomic factors on fruit and vegetable consumption in the households of Pakistan. Secondary data were used from a national-level survey, i.e. “Household Integrated Income and Consumption Survey” (HIICS) 2015-2016 published by the Pakistan Bureau of Statistics. A total of 11,187 households were included in the final analysis. Quantile regression models were applied to investigate the association between socioeconomic factors and the consumption of fruit and vegetable. More than half of the households in the sample did not meet the World Health Organization’s (WHO) recommended criteria for fruit and vegetable consumption, which is 400 g/day/capita. According to the quantile regression model, household income is an important factor in increasing fruit and vegetable intake because an increase in income leads to a greater likelihood of spending on healthy and nutritious foods. The increased consumption of fruit and vegetable was caused by the household head’s high education, which created multiple resources to increase income. Households in two provinces, i.e. Khyber Pakhtunkhwa and Baluchistan, have a greater impact on fruit and vegetable consumption than other provinces due to natural resource availability. Household size and dependency ratio hurt the consumption of fruit and vegetable because women and children are not able to do work. These results are very useful because a better understanding of the socioeconomic characteristics associated with fruit and vegetable intake could improve the effectiveness of policies aimed at increasing fruit and vegetable consumption and reducing the risk of chronic diseases.

PMID:36242534 | DOI:10.1080/19371918.2022.2134249

J Pharm Pract. 2022 Oct 14:8971900221134642. doi: 10.1177/08971900221134642. Online ahead of print.

ABSTRACT

Introduction: Pursuant to the COVID-19 pandemic, an executive order issued by the New York State (NYS) governor allowed pharmacists to act as laboratory directors for a limited-service laboratory (LSL) to order and perform Food and Drug Administration (FDA) and Emergency Use Authorization (EUA) Clinical Laboratory Improvement Amendment (CLIA)-waived COVID-19 point-of-care testing (POCT). Objectives: To (i) assess the status of NYS community pharmacists with POCT in the early stages of the COVID-19 pandemic, (ii) assess the readiness and willingness of community pharmacists to incorporate COVID-19 POCT into their workflow during a pandemic, and (iii) assess community pharmacists’ perception of the barrier to initiating COVID-19 POCT. Methods: This is a prospective cross-sectional study conducted from February 4 to February 21, 2021. An electronic survey consisting of 66 Likert-type questions, select all that apply, and fill-in-style questions were emailed to 250 Community Pharmacy Enhanced Service Network (CPESN) NY pharmacies, with a follow-up email sent halfway into the data collection period. The data were analyzed using descriptive statistics. Results: The result indicated that most participants (median = 5) demonstrated readiness and willingness to offer COVID-19 testing. Barriers to COVID-19 POCT were identified: impact on pharmacy workflow (59%), lack of payment mechanism (55%) and lack of sufficient training (21%). Most participants expressed interest in continuing POCT beyond the pandemic (86.1%). Conclusion: Community pharmacists in NYS reported willingness to initiate COVID-19 POCT. Addressing the identified barriers, such as workflow disruption and reimbursement challenges, will enable pharmacies to be better prepared to provide patient care, including POCT.

PMID:36242519 | DOI:10.1177/08971900221134642

Opt Express. 2022 Sep 12;30(19):34519-34532. doi: 10.1364/OE.465847.

ABSTRACT

The temporal characteristics of the free space optical communication (FSOC) turbulence fading channel are essential for analyzing the bit error rate (BER) performances and compiling the rationale of adaptive signal processing algorithms. However, the investigation is still limited since the majority of temporal sequence generation fails to combine the autocorrelation function (ACF) of the FSOC system parameters, and using the simplified formula results in the loss of detailed information for turbulence disturbances. In this paper, considering the ACF of engineering measurable atmospheric parameters, we propose a continuous-time FSOC channel fading sequence generation model that obeys the Gamma-Gamma (G-G) probability density function (PDF). First, under the influence of parameters such as transmission distance, optical wavelength, scintillation index, and atmospheric structural constant, the normalized channel fading models of ACF and PSD are established, and the numerical solution of the time-domain Gaussian correlation sequence is derived. Moreover, the light intensity generation model obeying the time-domain correlation with statistical distribution information is derived after employing the rank mapping, taking into account the association between the G-G PDF parameters and the large and small scales turbulence fading channels. Finally, the Monte Carlo numerical method is used to analyze the performances of the ACF, PDF, and PSD parameters, as well as the temporal characteristics of the generated sequence, and the matching relationships between these parameters and theory, under various turbulence intensities, propagation distances, and transverse wind speeds. Numerical results show that the proposed temporal sequence generation model highly restores the disturbance information in different frequency bands for the turbulence fading channels, and the agreement with the theoretical solution is 0.999. This study presents essential numerical simulation methods for analyzing and evaluating the temporal properties of modulated signals. When sophisticated algorithms are used to handle FSOC signals, our proposed temporal sequence model can provide communication signal experimental sample data generating techniques under various FSOC parameters, which is a crucial theoretical basis for evaluating algorithm performances.

PMID:36242462 | DOI:10.1364/OE.465847

Opt Express. 2022 Sep 12;30(19):34453-34467. doi: 10.1364/OE.469342.

ABSTRACT

We have proposed and demonstrated a denoising and extraction convolutional neural network (DECNN) composed of 1D denoising convolutional autoencoder (DCAE) and 1D residual attention network (RANet) modules to extract temperature and strain simultaneously in a Brillouin optical time-domain analysis (BOTDA) system. With DCAE for high-fidelity denoising and RANet for accurate and robust information extraction, integrated denoising and extraction of both temperature and strain have been realized for the first time under a single CNN framework. Both simulation and experiment have been conducted to statistically analyze the performance of the proposed scheme and compare it with the conventional equation solving method (CESM), which show that DECNN has large noise tolerance and robustness over a wide range of temperature/strain and signal-to-noise ratio (SNR) conditions. The mean standard deviation (SD) and root mean square error (RMSE) of the temperature/strain extracted by DECNN over a wide range of SNRs are only 0.2°C/9.7µɛ and 2°C/32.3µɛ at the end of 19.38 km long sensing fiber, respectively. At a relatively low SNR of 8.8 dB, DECNN shows 196 times better temperature/strain uncertainty and 146 times faster processing speed when compared with CESM.

PMID:36242457 | DOI:10.1364/OE.469342

Opt Express. 2022 Sep 12;30(19):34043-34052. doi: 10.1364/OE.466090.

ABSTRACT

Quantum-enhanced measurement technologies can unambiguously discriminate coherent states with accuracy beyond the classical heterodyne measurement. However, typical quantum-enhanced measurement scheme is vulnerable to the thermal noise, which will change the photon counting statistics of the coherent state. This paper presents a threshold-switching strategy that can discriminate quadrature phase-shift-keying coherent states with performance surpassing the typical quantum-enhanced scheme. In our scheme, photon number resolving detectors are used to switch the value of the threshold, which can mitigate the influence of thermal noise and other imperfections. Simulation results show that our scheme unambiguously discriminates the signal states with higher correct probability and the same error ratio compared with the typical scheme. Besides, this scheme can reduce the error ratio simultaneously for thermal noise N ≤ 0.2. The paper demonstrations that quantum-enhanced measurement with the threshold-switching strategy can adapt to different thermal noises by switching the value of the threshold under situations of different thermal noises and signal states.

PMID:36242426 | DOI:10.1364/OE.466090

Opt Express. 2022 Sep 12;30(19):34092-34105. doi: 10.1364/OE.468024.

ABSTRACT

As an effective tool for micro/nano-scale particle manipulation, plasmonic optical tweezers can be used to manipulate cells, DNA, and macromolecules. Related research is of great significance to the development of nanoscience. In this work, we investigated a sub-wavelength particle manipulation technique based on plasmonic optical tweezers. When the local plasmonic resonance is excited on the gold nanostructure arrays, the local electromagnetic field will be enhanced to generate a strong gradient force acting on nanoparticles, which could achieve particle sorting in sub-wavelength scale. On this basis, we explored the plasmonic enhancement effect of the sorting device and the corresponding optical force and optical potential well distributions. Additionally, the sorting effect of the sorting device was investigated in statistical methods, which showed that the sorting device could effectively sort particles of different diameters and refractive indices.

PMID:36242430 | DOI:10.1364/OE.468024

Opt Express. 2022 Sep 12;30(19):33826-33841. doi: 10.1364/OE.463682.

ABSTRACT

Underwater imaging is usually affected by water scattering and absorption, resulting in image blur and color distortion. In order to achieve color correction and dehazing for different underwater scenes, in this paper we report a fusion-based underwater image enhancement technique. First, statistics of the hue channel of underwater images are used to divide the underwater images into two categories: color-distorted images and non-distorted images. Then, category-specific combinations of color compensation and color constancy algorithms are used to remove the color shift. Second, a ground-dehazing algorithm using haze-line prior is employed to remove the haze in the underwater image. Finally, a channel-wise fusion method based on the CIE L* a* b* color space is used to fuse the color-corrected image and dehazed image. For experimental validation, we built a setup to acquire underwater images. The experimental results validate that the category-specific color correction strategy is robust to different categories of underwater images and the fusion strategy simultaneously removes haze and corrects color casts. The quantitative metrics on the UIEBD and EUVP datasets validate its state-of-the-art performance.

PMID:36242409 | DOI:10.1364/OE.463682

Opt Express. 2022 Aug 29;30(18):33048-33067. doi: 10.1364/OE.460495.

ABSTRACT

With the improvement of semiconductor processing technology, polarization sensors using division of focal plane have gradually become the mainstream method of polarization imaging. Similar to the color restoration method of the Bayer array sensor, the spatial information of polarized image is also recovered through the polarization demosaicking algorithm. In this paper, we propose a new modified Newton-residual interpolation polarization image demosaicking algorithm based on residual interpolation, which is suitable for a monochrome or color polarization filter array. First, we use the modified Newton interpolation method to generate edge-sensitive guiding images. Then, we carry out the improvement of the guide process during the residual interpolation by performing variance statistics on the local window image in the guiding process, so that the edges and flat image blocks have different guiding weights. Finally, we obtain edge-preserving results by applying these two improvements, which reduces the zipper effect and edge confusion. We compare the results of various algorithms on experimental data, demonstrating that our algorithm has impactful improvements in the evaluation metrics based on the ground-truth images.

PMID:36242354 | DOI:10.1364/OE.460495

Opt Express. 2022 Aug 29;30(18):32097-32109. doi: 10.1364/OE.467961.

ABSTRACT

We proposed and demonstrated an unprecedented high-efficiency Brillouin random fiber laser (BRFL) by fiber length optimization in a half-open linear cavity. In terms of the trade-off between Brillouin gain saturation and weak distributed Rayleigh feedback strength, optimal laser efficiency associated to proper fiber length in a BRFL was theoretically predicted. As a proof-of-concept, a unidirectional-pumped BRFL with a half-open linear cavity was experimentally conducted, in which a fiber Bragg grating at one end of gain fiber served as a high-reflection mirror while Rayleigh scattering enabled distributed feedback for random lasing resonance. Results show that the optimal fiber length of ∼3.4 km in the BRFL offers sufficient Rayleigh scattered random feedback whilst alleviating the Brillouin gain saturation to a large extent. Consequently, an optimal laser efficiency of 77.0% in the BRFL was experimentally demonstrated, which reaches the state-of-the-art high record. Laser characteristics, including the linewidth, statistics and frequency jitter were also systematically investigated. It is believed that such efficient BRFL could provide a promising platform for inspiring new explorations of laser physics as well as potentials in long-haul coherent communication and fiber-optic sensing.

PMID:36242278 | DOI:10.1364/OE.467961

Opt Express. 2022 Aug 15;30(17):31415-31438. doi: 10.1364/OE.460735.

ABSTRACT

The spectral distribution of marine remote sensing reflectance, R_rs, is the fundamental measurement of ocean color science, from which a host of bio-optical and biogeochemical properties of the water column can be derived. Estimation of uncertainty in these derived properties is thus dependent on knowledge of the uncertainty in satellite-retrieved R_rs (uc(R_rs)) at each pixel. Uncertainty in R_rs, in turn, is dependent on the propagation of various uncertainty sources through the R_rs retrieval process, namely the atmospheric correction (AC). A derivative-based method for uncertainty propagation is established here to calculate the pixel-level uncertainty in R_rs, as retrieved using NASA’s multiple-scattering epsilon (MSEPS) AC algorithm and verified using Monte Carlo (MC) analysis. The approach is then applied to measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, with uncertainty sources including instrument random noise, instrument systematic uncertainty, and forward model uncertainty. The uc(R_rs) is verified by comparison with statistical analysis of coincident retrievals from MODIS and in situ R_rs measurements, and our approach performs well in most cases. Based on analysis of an example 8-day global products, we also show that relative uncertainty in R_rs at blue bands has a similar spatial pattern to the derived concentration of the phytoplankton pigment chlorophyll-a (chl-a), and around 7.3%, 17.0%, and 35.2% of all clear water pixels (chl-a ≤ 0.1 mg/m³) with valid uc(R_rs) have a relative uncertainty ≤ 5% at bands 412 nm, 443 nm, and 488 nm respectively, which is a common goal of ocean color retrievals for clear waters. While the analysis shows that uc(R_rs) calculated from our derivative-based method is reasonable, some issues need further investigation, including improved knowledge of forward model uncertainty and systematic uncertainty in instrument calibration.

PMID:36242224 | DOI:10.1364/OE.460735