The effect of a therapeutic regimen of Traditional Chinese Medicine rehabilitation for post-stroke cognitive impairment: study protocol for a randomized controlled trial

Background Post-stroke cognitive impairment (PSCI) lessens quality of life, restricts the rehabilitation of stroke, and increases the social and economic burden stroke imposes on patients and their families. Therefore effective treatment is of paramount importance. However, the treatment of PSCI is very limited. The primary aim of this protocol is to propose a lower cost and more effective therapy, and to confirm the long-term effectiveness of a therapeutic regimen of Traditional Chinese Medicine (TCM) rehabilitation for PSCI. Methods/Design A prospective, multicenter, large sample, randomized controlled trial will be conducted. A total of 416 eligible patients will be recruited from seven inpatient and outpatient stroke rehabilitation units and randomly allocated into a therapeutic regimen of TCM rehabilitation group or cognitive training (CT) control group. The intervention period of both groups will last 12 weeks (30 minutes per day, five days per week). Primary and secondary outcomes will be measured at baseline, 12 weeks (at the end of the intervention), and 36 weeks (after the 24-week follow-up period). Discussion This protocol presents an objective design of a multicenter, large sample, randomized controlled trial that aims to put forward a lower cost and more effective therapy, and confirm the long-term effectiveness of a therapeutic regimen of TCM rehabilitation for PSCI through subjective and objective assessments, as well as highlight its economic advantages

Impact of Assimilating Advanced Himawari Imager Channel 16 Data on Precipitation Prediction over the Haihe River Basin

Assimilation of high-resolution geostationary satellite data is of great value for precise precipitation prediction in regional basins. The operational geostationary satellite imager carried by the Himawari-8 satellite, Advanced Himawari Imager (AHI), has two additional water vapor channels and four other channels compared with its predecessor, MTSAT-2. However, due to the uncertainty in surface parameters, AHI surface-sensitive channels are usually not assimilated over land, except for the three water vapor channels. Previous research showed that the brightness temperature of AHI channel 16 is much more sensitive to the lower-tropospheric temperature than to surface emissivity, which is similar to the three water vapor channels 8–10. As a follow-up work, this paper evaluates the effectiveness of assimilating brightness temperature observations over land from both the three AHI water vapor channels and channel 16 to improve watershed precipitation forecasting through both case analysis (in the Haihe River basin, China) and batch tests. It is found that assimilating AHI channel 16 can improve the upstream near-surface atmospheric temperature forecast, which in turn affects the development of downstream weather systems. The precipitation forecasting test results indicate that adding the terrestrial observations of channel 16 to the assimilation of AHI data can improve short-term precipitation forecasting in the basin

Comparative Analysis of the Observation Bias and Error Characteristics of AGRI and AHI Data for Land Areas in East Asia

Observation bias and error characteristics are the preconditions for the effective assimilation of observation data. In this paper, the bias and error characteristics of the AHI (Advanced Himawari Imager (AHI) and AGRI (Multi-Channel Advanced Geostationary Orbit Radiation Imager (AGRI) data are compared and analyzed, with an emphasis on the observations obtained from land areas. The results show that the observation errors of the two instruments for the ocean area have a good channel consistency over ocean areas, which are all with errors of about 0.6 K; however, the bias and error are significantly affected by the land-surface types and terrain heights over land. For most of the AHI channels, the bias in urban-area bias is smaller than that of those of other surface types, while that of the AGRI data exhibits just the opposite trend, with obviously larger biases in urban areas. However, the observation errors of these two instruments in urban areas are significantly smaller than those of other surface types. The biases of the two instruments do not extensively change much with the terrain height, only slightly decreasing when the height is above 1000 m; however, the observation errors increase obviously with the increase of terrain heights. The difference between the two instruments is that the observation error of the AHI data tends to be stable and stabilizes above 1000 m, while that of the AGRI data is relatively stable below 500 m. The observation errors of the CO2-sensitive channels of the two instruments over the land areas are obviously smaller than those of other near-surface channels, which may indicate that the data obtained in these two CO2 channels have good application prospects for assimilation over land

Iron-Mediated Carboarylation/Cyclization of Propargylanilines with Acetals: A Concise Route to Indeno[2,1-c]quinolines

FeCl3- and FeBr3-mediated tandem carboarylation/cyclization of propargylanilines with diethyl benzaldehyde acetals furnished the tetracyclic core of indeno[2,1-c]quinolines. 5-Tosyl-6,7-dihydro-5H-indeno[2,1-c]quinoline and 7H-indeno[2,1-c]quinoline derivatives were obtained in good to excellent yields, respectively, by tuning the FeX3 loadings and/or reaction temperatures

Synthesis of Small Ce3+-Er3+-Yb3+ Tri-Doped BaLuF5 Active-Core-Active-Shell-Active-Shell Nanoparticles with Strong Down Conversion Luminescence at 1.5 μm

Small fluoride nanoparticles (NPs) with strong down-conversion (DC) luminescence at 1.5 μm are quite desirable for optical fiber communication systems. Nevertheless, a problem exists regarding how to synthesize small fluoride NPs with strong DC emission at 1.5 μm. Herein, we propose an approach to improve 1.5 μm emission of BaLuF5:Yb3+,Er3+ NPs by way of combining doping Ce3+ ions and coating multiple BaLuF5: Yb3+ active-shells. We prepared the BaLuF5:18%Yb3+,2%Er3+,2%Ce3+ NPs through a high-boiling solvent method. The effect of Ce3+ concentration on the DC luminescence was systematically investigated in the BaLuF5:Yb3+,Er3+ NPs. Under a 980 nm laser excitation, the intensities of 1.53 μm emission of BaLuF5:18%Yb3+,2%Er3+,2%Ce3+ NPs was enhanced by 2.6 times comparing to that of BaLuF5:18%Yb3+,2%Er3+ NPs since the energy transfer between Er3+ and Ce3+ ions: Er3+:4I11/2 (Er3+) + 2F5/2 (Ce3+) → 4I13/2 (Er3+) + 2F7/2 (Ce3+). Then, we synthesized BaLuF5:18%Yb3+,2%Er3+,2%Ce3+@BaLuF5:5%Yb3+@BaLuF5:5%Yb3+ core-active-shell-active-shell NPs via a layer-by-layer strategy. After coating two BaLuF5:Yb3+ active-shell around BaLuF5:Yb3+,Er3+,Ce3+ NPs, the intensities of the 1.53 μm emission was enhanced by 44 times compared to that of BaLuF5:Yb3+,Er3+ core NPs, since the active-shells could be used to not only suppress surface quenching but also to transfer the pump light to the core region efficiently through Yb3+ ions inside the active-shells

Development and Evaluation of AMSU-A Cloud Detection over the Tibetan Plateau

Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) data have been widely assimilated in operational forecasting systems. However, effective distinction between cloudy and clear-sky data is still an essential prerequisite for the assimilation of microwave observations. Cloud detection over the Tibetan Plateau has long been a challenge owing to the influence of low temperatures, terrain height, surface vegetation, and inaccurate background fields. Based on the variations in the response characteristics of different channels of AMSU-A to clouds, five AMSU-A window and low-peaking channels (channels 1–4 and 15) are chosen to establish a cloud detection index. Combined with the existing MHS cloud detection index, a cloud detection scheme over the Tibetan Plateau is proposed. Referring to VISSR-II (Stretched Visible and Infrared Spin Scan Radiometer-II) and CALIPSO (The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) cloud classification products, the detection rate of cloudy data and the rejection rate of clear-sky data under different cloud index thresholds are evaluated. Results show that the new cloud detection scheme can identify more than 80% of cloudy data on average, but this decreases to 72% for area with terrain higher than 5 km, and the false deletion rate remains stable at 45%. The detection rates of mixed clouds and cumulonimbus are higher than 90%, but it is lower than 50% for altostratus with an altitude of about 7–8 km. Comparative analysis shows that the new method is more suitable for areas with terrain higher than 700 m. Based on the cloud detection results, the effects of terrain height on the characteristics of observation error and bias are also discussed for AMSU-A channels 5 and 6