Image3_Impact of the Pilot Volume-Based Drug Purchasing Policy in China: Interrupted Time-Series Analysis with Controls.TIFF by Yilin Chen (678552)

“…Overall, in pilot cities, there was a 35% (95%-CI: 28–41%, p < 0.001) decrease in the purchase spending for all drugs in the first post-policy month, from 8.1 billion CNY estimated in the absence of VBP down to 5.3 billion CNY; in control cities, the change was negligible. …”

Image3_Impact of the Pilot Volume-Based Drug Purchasing Policy in China: Interrupted Time-Series Analysis with Controls.tif by Yilin Chen (678552)

“…Overall, in pilot cities, there was a 35% (95%-CI: 28–41%, p < 0.001) decrease in the purchase spending for all drugs in the first post-policy month, from 8.1 billion CNY estimated in the absence of VBP down to 5.3 billion CNY; in control cities, the change was negligible. …”

Image3_Impact of the Pilot Volume-Based Drug Purchasing Policy in China: Interrupted Time-Series Analysis with Controls.tif by Yilin Chen (678552)

“…Overall, in pilot cities, there was a 35% (95%-CI: 28–41%, p < 0.001) decrease in the purchase spending for all drugs in the first post-policy month, from 8.1 billion CNY estimated in the absence of VBP down to 5.3 billion CNY; in control cities, the change was negligible. …”

Image2_Impact of the Pilot Volume-Based Drug Purchasing Policy in China: Interrupted Time-Series Analysis with Controls.tif by Yilin Chen (678552)

“…Overall, in pilot cities, there was a 35% (95%-CI: 28–41%, p < 0.001) decrease in the purchase spending for all drugs in the first post-policy month, from 8.1 billion CNY estimated in the absence of VBP down to 5.3 billion CNY; in control cities, the change was negligible. …”

Image2_Impact of the Pilot Volume-Based Drug Purchasing Policy in China: Interrupted Time-Series Analysis with Controls.tif by Yilin Chen (678552)

“…Overall, in pilot cities, there was a 35% (95%-CI: 28–41%, p < 0.001) decrease in the purchase spending for all drugs in the first post-policy month, from 8.1 billion CNY estimated in the absence of VBP down to 5.3 billion CNY; in control cities, the change was negligible. …”

Image2_Impact of the Pilot Volume-Based Drug Purchasing Policy in China: Interrupted Time-Series Analysis with Controls.TIFF by Yilin Chen (678552)

“…Overall, in pilot cities, there was a 35% (95%-CI: 28–41%, p < 0.001) decrease in the purchase spending for all drugs in the first post-policy month, from 8.1 billion CNY estimated in the absence of VBP down to 5.3 billion CNY; in control cities, the change was negligible. …”

(a)–(d) depict the time derivation of the average investing strategies for different time-horizons. by Jan Jurczyk (3162819)

“…<p>In (a) with <i>ω</i> = 1 year the three major crisis in the time from 2003 until 2016 exhibit the three largest drops. …”

Dsh and Rac Modulate JNK Activation by Mohammed Srahna (66143)

“…</p> <p>(H) Heads from Canton S, <i>dsh¹/+, dsh¹/dsh¹, dsh¹/dsh¹;; RacJ11,Rac2</i>^Δ<i>FRT80,Mtl</i>^Δ adults animals were lysed, and whole-head lysates were subjected to SDS-PAGE. …”

Disinhibition of butyrate by addition of acetate, light and a mix of acetate/butyrate due to the biomass effect. by Caroline Baroukh (612077)

“…<p>A larger biomass implies a decrease in butyrate inhibition on growth. …”

Crop yield and ruminant feed efficiency assumptions in the different scenarios by H Valin (557174)

“…<p><b>Table 1.</b>  Crop yield and ruminant feed efficiency assumptions in the different scenarios. …”

Potential site-specific management actions to reduce bleaching under simulated thermal stress using best-fit model. by Morgan Winston (10887384)

“…<p>Colors reflect the variable found to result in the largest decrease in predicted bleaching (%) at the site-level under model perturbations, wherein all variables were in turn reduced by 1 SD as other variables were held at observed values. …”

Monte Carlo studies on photon interactions in radiobiological experiments by Mehrdad Shahmohammadi Beni (3591221)

“…Bulges in the interaction fractions (versus water medium thickness) were observed, which reflected the changes in the energies of the propagating photons as a result of the water medium thickness as well as the energy-dependent photon interaction cross-sections. (2) Photoelectric interaction and incoherent scattering dominated for lower-energy (10 keV) and higher-energy (100 keV and 1 MeV) incident photons. (3) The fractions of electron ejection from different nuclei were mainly governed by the photoelectric effect cross-sections, and the fractions from the 1s subshell were the largest. (4) The penetration fractions in general decreased with increasing medium thickness, and increased with increasing incident photon energy, the latter being explained by the corresponding reduction in interaction cross-sections. (5) The area under the angular distributions of photons exiting medium layer and then interacting with cell layer decreased with increasing incident photon energy. (6) The number of cells suffering at least one electron hit increased with the administrated dose. …”

Supplementary Material for: Lack of Association between Pretransplant Donor-Specific Antibodies and Posttransplant Kidney Outcomes in Simultaneous Liver-Kidney Transplant Recipient... by Yazawa M. (8343324)

“…<b><i>Introduction and Objective:</i></b> The impact of pretransplant donor-specific antibodies (DSAs), especially class II DSAs, on kidney allograft outcomes remains unclear in simultaneous liver-kidney transplantation (SLKT) recipients. …”

Image_2_Postmortem skin microbiome signatures associated with human cadavers within the first 12 h at the morgue.pdf by Lavinia Iancu (16652904)

“…However, there were no significant differences in taxonomic profiles between collection time, T0 and T1, except for some dynamic changes in the abundance of dominant bacteria. …”

Coarse-grained model leads to collective behavior. by Giovanna De Palo (476510)

“…<p>(A) Screenshot of simulation for <i>n</i> = 1,000 cells at different time points: prestreaming (left), streaming (center), and after aggregation (right). …”

Image 1_Computer-vision based automatic rider helmet violation detection and vehicle identification in Indian smart city scenarios using NVIDIA TAO toolkit and YOLOv8.jpg by Uttam U. Deshpande (21758837)

“…Experimental analysis shows that our proposed two-step model achieved a promising helmet detection accuracy of 98.56% and a 97.6% number plate detection accuracy of persons not wearing helmets. …”

Image 6_Computer-vision based automatic rider helmet violation detection and vehicle identification in Indian smart city scenarios using NVIDIA TAO toolkit and YOLOv8.jpg by Uttam U. Deshpande (21758837)

“…Experimental analysis shows that our proposed two-step model achieved a promising helmet detection accuracy of 98.56% and a 97.6% number plate detection accuracy of persons not wearing helmets. …”

Image 7_Computer-vision based automatic rider helmet violation detection and vehicle identification in Indian smart city scenarios using NVIDIA TAO toolkit and YOLOv8.jpg by Uttam U. Deshpande (21758837)

“…Experimental analysis shows that our proposed two-step model achieved a promising helmet detection accuracy of 98.56% and a 97.6% number plate detection accuracy of persons not wearing helmets. …”

Development of CuAg/Cu2O nanoparticles on carbon nitride surface for methanol oxidation and selective conversion of carbon dioxide into formate by Nazir, Roshan

“…A probable reason may be the strain induced by alloy formation which could favor a reduced coverage of adsorbed hydrogen and a decrease in oxophilicity of the compressively strained copper.…”
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Evacuation under flooded conditions: Experimental investigation of the influence of water depth on walking behaviors by Dias, Charitha

“…To propose guidelines for evacuation planning during floods and to develop simulation tools, which can be used in evacuation planning, empirical data are needed under different flooding conditions. However, there is a lack of data and studies on such aspects. This study examines the influence of water depth on human walking behaviors under hydrostatic conditions using the data collected through a controlled laboratory experiment. …”
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