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Both low FODMAP diet and GDA in patients with IBS-D led to adequate improvement of gastrointestinal symptoms for 6 weeks. However, the low FODMAP diet has greater benefits in IBS improvement.

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The existing video coding standards such as H.264/AVC and High Efficiency Video Coding (HEVC) have been designed based on the statistical properties of Low Dynamic Range (LDR) videos and are not accustomed to the characteristics of High Dynamic Range (HDR) content. In this study, we investigate the performance of the latest LDR video compression standard, HEVC, as well as the recent widely commercially used video compression standard, H.264/AVC, on HDR content. Subjective evaluations of results on an HDR display show that viewers clearly prefer the videos coded via an HEVC-based encoder to the ones encoded using an H.264/AVC encoder. In particular, HEVC outperforms H.264/AVC by an average of 10.18% in terms of mean opinion score and 25.08% in terms of bit rate savings.

Standard image quality metrics, such as PSNR or SSIM, cannot be directly computed on linear high dynamic range colour values because such values non-linearly related to our perception of visible differences. In this work, we develop a new encoding function (PU21) to convert absolute high dynamic range (HDR) linear colour values into approximately perceptually uniform (PU) values, which can be used with standard quality metrics. The proposed PU21 function is based on a recent contrast sensitivity model, fitted to the measurements up to 10 000 cd/m 2 . Unlike the conventional simplified approach of deriving PU functions based on peak sensitivities, we model realistic coding artefacts to find visibility thresholds for our derivation. Furthermore, the new PU accounts for the effect of glare on image quality. The proposed PU21 improves the accuracy of quality predictions for standard metrics of PSNR, VSI, FSIM, SSIM, and MS-SSIM in their correlation with subjective scores on HDR images included in UPIQ, one of the largest HDR image quality datasets.

10.30699/jambs.29.135.238 Background & Objective: In December 2019, the outbreak of coronavirus disease 2019 (COVID-19) was observed in China, and it it spread rapidly throughout the world. Iranian traditional healers have applied different medicinal plants to prevent and treat COVID-19 based on their ethnopharmacological knowledge. This research aimed to investigate the ethnomedicinal knowledge of Iranian traditional healers to alleviate COVID-19 signs and symptoms. Materials & Methods: Due to the limitations caused by COVID-19 pandemic, oral interviews were conducted by 26 traditional healers in Kerman and Zahedan cities in Iran. The names of recommended remedies for COVID-19 were collected, and their scientific names were authenticated. Next, a comprehensive research was carried out in the scientific databases. Finally, the herbs with any related proved properties to the respiratory system were listed; these herbs were probably useful for the COVID-19 prevention or treatment. Results: Zataria multiflora, Althaea officinalis, Hordeum vulgare, Malva sylvestris, Matricaria chamomilla, Glycyrrhiza glabra, Allium sativum and Zingiber officinale are considered as the most popular herbs by Iranian traditional healers for prevention and/or treatment of COVID-19. Recent studies have demonstrated that the abovementioned herbs can be considered as good sources for alleviating the respiratory disorders such as influenza. Moreover, they have antitussive and immune-modulatory properties. Conclusion:Since there is no effective treatment for COVID-19, the capacity of different traditional medicine and ethnomedicine knowledge can be used as good sources for new drug discovery after accurate studies.

Background Quality of care is gaining increasing attention in research, clinical practice, and health care planning. Methods for quality assessment and monitoring, such as quality indicators (QIs), are needed to ensure health services in line with norms and recommendations. The aim of this study was to assess the responsiveness of a newly developed QI set for rehabiliation for people with rheumatic and musculoskeletal diseases (RMDs). Methods We used two yes/no questionnaires to measure quality from both the provider and patient perspectives, scored in a range of 0–100% (best score, 100%). We collected QI data from a multicenter stepped-wedge cluster-randomized controlled trial (the BRIDGE trial) that compared traditional rehabilitation with a new BRIDGE program designed to improve quality and continuity in rehabilitation. Assessment of the responsiveness was performed as a pre–post evaluation: Providers at rehabilitation centers in Norway completed the center-reported QIs (n = 19 structure indicators) before (T1) and 6–8 weeks after (T2) adding the BRIDGE intervention. The patient-reported QIs comprised 14 process and outcomes indicators, measuring quality in health services from the patient perspective. Pre-intervention patient-reported data were collected from patients participating in the traditional program (T1), and post-intervention data were collected from patients participating in the BRIDGE program (T2). The patient groups were comparable. We used a construct approach, with a priori hypotheses regarding the expected direction and magnitude of PR changes between T1 and T2. For acceptable responsivess, at least 75% of the hypotheses needed to be confirmed. Results All eight participating centers and 82% of the patients (293/357) completed the QI questionnaires. Responsiveness was acceptable, with 44 of 53 hypotheses (83%) confirmed for single indicators and 3 of 4 hypotheses (75%) confirmed for the sum scores. Conclusion We found this QI set for rehabilitation to be responsive when applied in rehabilitation services for adults with various RMD conditions. We recommend this QI set as a timely method for establishing quality-of-rehabilitation benchmarks, promoting important progress toward high-quality rehabilitation, and tracking trends over time. Trial registration The study is part of the larger BRIDGE trial, registered at ClinicalTrials.gov (Identifier: NCT03102814).

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