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Photosynthetically active radiation is a key parameter for determining crop yield. Separating photosynthetically active radiation into direct and diffuse components is significant to agrivoltaic systems. The varying shading conditions caused by the solar panels produce a higher contribution of diffuse irradiance reaching the crops. This study introduces a new separation model capable of accurately estimating the diffuse component from the global photosynthetically active radiation and conveniently retrievable meteorological parameters. The model modifies one of the highest-performing separation models for broadband irradiance, namely, the Yang2 model. Four new predictors are added: atmospheric optical thickness, vapor pressure deficit, aerosol optical depth, and surface albedo. The proposed model has been calibrated, tested, and validated at three sites in Sweden with latitudes above 58 °N, outperforming four other models in all examined locations, with R2 values greater than 0.90. The applicability of the developed model is demonstrated using data retrieved from Sweden's first agrivoltaic system. A variety of data availability cases representative of current and future agrivoltaic systems is tested. If on-site measurements of diffuse photosynthetically active radiation are not available, the model calibrated based on nearby stations can be a suitable first approximation, obtaining an R2 of 0.89. Utilizing predictor values derived from satellite data is an alternative method, but the spatial resolution must be considered cautiously as the R2 dropped to 0.73. [ABSTRACT FROM AUTHOR]

• Seven stand-alone decomposition models for solar radiation are applied to PAR. • Comparison and re-parameterization are performed against measured PAR values in three locations in Sweden. • The best-performing decomposition model is Y ang2 with nRMSE of 23.75% in Norunda. • For agrivoltaic studies, S tarke model is suggested if satellite data cannot be retrieved. • EMOS approach is explored and provides further accuracy (nRMSE of 23.02% in Norunda) Decomposition models of solar irradiance estimate the magnitude of diffuse horizontal irradiance from global horizontal irradiance. These two radiation components are well known to be essential for predicting the performance of solar photovoltaic systems. In open-field agrivoltaic systems (i.e., the dual use of land for both agricultural activities and solar power conversion), cultivated crops receive unequal amounts of direct, diffuse, and reflected photosynthetically active radiation (PAR). These uneven amounts depend on where the crops are growing due to the non-homogenous shadings caused by the presence of the installed solar panels (above the crops or vertically mounted). It is known that, per unit of total PAR, diffuse PAR is more efficient for canopy photosynthesis than is direct PAR. For this reason, it is essential to estimate the diffuse PAR component when agrivoltaic systems are being assessed, in order to properly predict the crop yield. Since PAR is the electromagnetic radiation in the 400–700 nm waveband that can be used for photosynthesis by the crops, several stand-alone decomposition models typically used to split global horizontal irradiance are selected in this study to decompose PAR into direct and diffuse. These models are applied and validated in three locations in Sweden (Lanna, Hyltemossa and Norunda) using the coefficients stated on the models' original publications and locally fitted coefficients. The results showed weaker performances in all stand-alone models for non-locally fitted coefficients (nRMSE ranging from 27% to 43%). However, performances improve with re-parameterization, with a highest nRMSE of 35.24% in Lanna. The Y ang2 decomposition model is the best-performing one, with the lowest nRMSE of 23.75% in Norunda when applying re-estimated coefficients. Country level sets of coefficients for the best-performing models (Y ang2 and S tarke) are given after parameterization using combined data for all three locations in Sweden. These Sweden-fitted models are tested and show an nRMSE of 25.08% (Y ang2) and 28.60% (S tarke). These results can be used to perform estimations of the PAR diffuse component in Sweden wherever ground measurements are not available. The overall methodology can be similarly applied to other countries. [ABSTRACT FROM AUTHOR]

Background: In both Russia and Sweden, the dominant hepatitis C virus (HCV) is genotype 1, but around one-third of patients have genotype 3 infection. For such countries, HCV genotype testing is recommended prior to therapy. An effective pangenotypic therapy may potentially eliminate the need for genotyping. In this study, we evaluated the efficacy and safety of sofosbuvir/velpatasvir for 12 weeks in patients from Russia and Sweden., Methods: In an open-label, single-arm phase-3 study, patients could have HCV genotype 1-6 infection and were treatment-naïve or interferon treatment-experienced. All patients received sofosbuvir/velpatasvir, once daily for 12 weeks. The primary endpoint was sustained virologic response 12 weeks post-treatment (SVR12)., Results: Of 122 patients screened, 119 were enrolled and treated. Overall, half (50%) were male, 18% had cirrhosis, and 24% had failed prior interferon-based therapy. In total, 66% of patients were infected with HCV genotype 1 (59% 1b and 7% 1a), 6% with genotype 2, and 29% with genotype 3. The overall SVR12 rate was 99% (118/119, 95% confidence interval 95-100%). One treatment-experienced patient infected with HCV genotype 3 experienced virologic relapse after completing treatment. The most common adverse events were headache (16%) and fatigue (7%). Serious adverse events were observed in four patients, but none were related to treatment. No patients discontinued treatment due to adverse events., Conclusion: Sofosbuvir/velpatasvir as a pangenotypic treatment for 12 weeks was highly effective in patients from Russia and Sweden infected with HCV genotypes 1, 2, or 3. Sofosbuvir/velpatasvir was safe and well-tolerated. Clinical trial number: ClinicalTrials.gov NCT02722837.