While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial ac...While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial accuracy. This is particularly true for research focused on the evaluation of adaptive forest management strategies. In this study, we developed an application, Climate AP, to generate scale-free(i.e., specific to point locations) climate data for historical(1901–2015) and future(2011–2100)years and periods. Climate AP uses the best available interpolated climate data for the reference period 1961–1990 as baseline data. It downscales the baseline data from a moderate spatial resolution to scale-free point data through dynamic local elevation adjustments. It also integrates and downscales the historical and future climate data using a delta approach. In the case of future climate data, two greenhouse gas representative concentration pathways(RCP 4.5 and 8.5) and 15 general circulation models are included to allow for the assessment of alternative climate scenarios. In addition, Climate AP generates a large number of biologically relevant climate variables derived from primary monthly variables. The effectiveness of the local downscaling was determined based on the strength of the local linear regression for the estimate of lapse rate. The accuracy of the Climate AP output was evaluated through comparisons of Climate AP output against observations from 1805 weather stations in the Asia Pacific region. The local linear regression explained 70%–80% and 0%–50% of the total variation in monthly temperatures and precipitation, respectively, in most cases. Climate AP reduced prediction error by up to27% and 60% for monthly temperature and precipitation,respectively, relative to the original baselines data. The improvements for baseline portions of historical and futurewere more substantial. Applications and limitations of the software are discussed.展开更多
The Relative Pollen Productivities(RPPs)of common steppe species are estimated using Extended R-value(ERV)model based on pollen analysis and vegetation survey of 30 surface soil samples from typical steppe area of nor...The Relative Pollen Productivities(RPPs)of common steppe species are estimated using Extended R-value(ERV)model based on pollen analysis and vegetation survey of 30 surface soil samples from typical steppe area of northern China.Artemisia,Chenopodiaceae,Poaceae,Cyperaceae,and Asteraceae are the dominant pollen types in pollen assemblages,reflecting the typical steppe communities well.The five dominant pollen types and six common types(Thalictrum,Iridaceae,Potentilla,Ephedra,Brassicaceae,and Ulmus)have strong wind transport abilities;the estimated Relevant Source Area of Pollen(RSAP)is ca.1000 m when the sediment basin radius is set at 0.5 m.Ulmus,Artemisia,Brassicaceae,Chenopodiaceae,and Thalictrum have relative high RPPs;Poaceae,Cyperaceae,Potentilla,and Ephedra pollen have moderate RPPs;Asteraceae and Iridaceae have low RPPs.The reliability test of RPPs revealed that most of the RPPs are reliable in past vegetation reconstruction.However,the RPPs of Asteraceae and Iridaceae are obviously underestimated,and those of Poaceae,Chenopodiaceae,and Ephedra are either slightly underestimated or slightly overestimated,suggesting that those RPPs should be considered with caution.These RPPs were applied to estimating plant abundances for two fossil pollen spectra(from the Lake Bayanchagan and Lake Haoluku)covering the Holocene in typical steppe area,using the"Regional Estimates of Vegetation Abundance from Large Sites"(REVEALS)model.The RPPs-based vegetation reconstruction revealed that meadow-steppe dominated by Poaceae,Cyperaceae,and Artemisia plants flourished in this area before 6500–5600 cal yr BP,and then was replaced by present typical steppe.展开更多
The key challenge of industrial water electrolysis is to design catalytic electrodes that can stabilize high current density with low power consumption(i.e.,overpotential),while industrial harsh conditions make the ba...The key challenge of industrial water electrolysis is to design catalytic electrodes that can stabilize high current density with low power consumption(i.e.,overpotential),while industrial harsh conditions make the balance between electrode activity and stability more difficult.Here,we develop an efficient and durable electrode for water oxidation reaction(WOR),which yields a high current density of 1000 mA cm−2 at an overpotential of only 284 mV in 1M KOH at 25°C and shows robust stability even in 6M KOH strong alkali with an elevated temperature up to 80°C.This electrode is fabricated from a cheap nickel foam(NF)substrate through a simple one-step solution etching method,resulting in the growth of ultrafine phosphorus doped nickel-iron(oxy)hydroxide[P-(Ni,Fe)O_(x)H_(y)]nanoparticles embedded into abundant micropores on the surface,featured as a self-stabilized catalyst–substrate fusion electrode.Such self-stabilizing effect fastens highly active P-(Ni,Fe)O_(x)H_(y)species on conductive NF substrates with significant contribution to catalyst fixation and charge transfer,realizing a win–win tactics for WOR activity and durability at high current densities in harsh environments.This work affords a cost-effective WOR electrode that can well work at large current densities,suggestive of the rational design of catalyst electrodes toward industrial-scale water electrolysis.展开更多
BACKGROUND The minimal clinically important difference(MCID)is defined as the smallest meaningful change in a health domain that a patient would identify as important.Thus,an improvement that exceeds the MCID can be u...BACKGROUND The minimal clinically important difference(MCID)is defined as the smallest meaningful change in a health domain that a patient would identify as important.Thus,an improvement that exceeds the MCID can be used to define a successful treatment for the individual patient.AIM To quantify the rate of clinical improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis.METHODS Patients were treated with the Global Unite total shoulder platform arthroplasty between March 2017 and February 2019 at Herlev and Gentofte Hospital,Denmark.The patients were evaluated preoperatively and 3 months,6 months,12 months,and 24 months postoperatively using the Western Ontario Osteoarthritis of the Shoulder index(WOOS),Oxford Shoulder Score(OSS)and Constant-Murley Score(CMS).The rate of clinically relevant improvement was defined as the proportion of patients who had an improvement 24 months postoperatively that exceeded the MCID.Based on previous literature,MCID for WOOS,OSS,and CMS were defined as 12.3,4.3,and 12.8 respectively.RESULTS Forty-nine patients with a Global Unite total shoulder platform arthroplasty were included for the final analysis.Mean age at the time of surgery was 66 years(range 49.0-79.0,SD:8.3)and 65%were women.One patient was revised within the two years follow-up.The mean improvement from the preoperative assessment to the two-year follow-up was 46.1 points[95%confidence interval(95%CI):39.7-53.3,P<0.005]for WOOS,18.2 points(95%CI:15.5-21.0,P<0.005)for OSS and 37.8 points(95%CI:31.5-44.0,P<0.005)for CMS.Two years postoperatively,41 patients(87%)had an improvement in WOOS that exceeded the MCID,45 patients(94%)had an improvement in OSS that exceeded the MCID,and 42 patients(88%)had an improvement in CMS that exceeded the MCID.CONCLUSION Based on three shoulder-specific outcome measures we find that approximately 90%of patients has a clinically relevant improvement.This is a clear message when informing patients about their prognosis.展开更多
Sampling-based planning algorithm is a powerful tool for solving planning problems in highdimensional state spaces.In this article,we present a novel approach to sampling in the most promising regions,which significan...Sampling-based planning algorithm is a powerful tool for solving planning problems in highdimensional state spaces.In this article,we present a novel approach to sampling in the most promising regions,which significantly reduces planning time-consumption.The RRT#algorithm defines the Relevant Region based on the cost-to-come provided by the optimal forward-searching tree.However,it uses the cumulative cost of a direct connection between the current state and the goal state as the cost-to-go.To improve the path planning efficiency,we propose a batch sampling method that samples in a refined Relevant Region with a direct sampling strategy,which is defined according to the optimal cost-to-come and the adaptive cost-to-go,taking advantage of various sources of heuristic information.The proposed sampling approach allows the algorithm to build the search tree in the direction of the most promising area,resulting in a superior initial solution quality and reducing the overall computation time compared to related work.To validate the effectiveness of our method,we conducted several simulations in both SE(2)and SE(3)state spaces.And the simulation results demonstrate the superiorities of proposed algorithm.展开更多
Objective： To investigate the clinical effects of electroacupuncture （EA） on the head points for improving gnosia in patients with vascular dementia （VD）. Methods： 90 VD patients were randomly divided into a dru...Objective： To investigate the clinical effects of electroacupuncture （EA） on the head points for improving gnosia in patients with vascular dementia （VD）. Methods： 90 VD patients were randomly divided into a drug group, an EA group and an EA plus drug group. Scoring with the M/VISE scale and detecting the relevant potentials were done before treatment and after a 6-week treatment. Results： Gnosia was improved after treatment in all the three groups with no significant difference by the intergroup comparison. Conclusion： The above three therapies can all improve gnosia, reduce the psychological stress, strengthen attention and shorten the awaiting time for recognition; and EA plus Nimodipine seems to be the best in the curative effect.展开更多
基金funded by a research grant"Adaptation of Asia-Pacific Forests to Climate Change"(APFNet/2010/PPF/001)funded by the Asia-Pacific Network for Sustainable Forest Management and Rehabilitation
文摘While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial accuracy. This is particularly true for research focused on the evaluation of adaptive forest management strategies. In this study, we developed an application, Climate AP, to generate scale-free(i.e., specific to point locations) climate data for historical(1901–2015) and future(2011–2100)years and periods. Climate AP uses the best available interpolated climate data for the reference period 1961–1990 as baseline data. It downscales the baseline data from a moderate spatial resolution to scale-free point data through dynamic local elevation adjustments. It also integrates and downscales the historical and future climate data using a delta approach. In the case of future climate data, two greenhouse gas representative concentration pathways(RCP 4.5 and 8.5) and 15 general circulation models are included to allow for the assessment of alternative climate scenarios. In addition, Climate AP generates a large number of biologically relevant climate variables derived from primary monthly variables. The effectiveness of the local downscaling was determined based on the strength of the local linear regression for the estimate of lapse rate. The accuracy of the Climate AP output was evaluated through comparisons of Climate AP output against observations from 1805 weather stations in the Asia Pacific region. The local linear regression explained 70%–80% and 0%–50% of the total variation in monthly temperatures and precipitation, respectively, in most cases. Climate AP reduced prediction error by up to27% and 60% for monthly temperature and precipitation,respectively, relative to the original baselines data. The improvements for baseline portions of historical and futurewere more substantial. Applications and limitations of the software are discussed.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA05120202)the National Natural Science Foundation of China(Grant Nos.41071132,41371215)+1 种基金Science and Technology Department of Hebei Province(Grant No.13277611D)the Foundation of Key Discipline of Hebei Province and Hebei Key Laboratory of Environmental Change and Ecological Construction
文摘The Relative Pollen Productivities(RPPs)of common steppe species are estimated using Extended R-value(ERV)model based on pollen analysis and vegetation survey of 30 surface soil samples from typical steppe area of northern China.Artemisia,Chenopodiaceae,Poaceae,Cyperaceae,and Asteraceae are the dominant pollen types in pollen assemblages,reflecting the typical steppe communities well.The five dominant pollen types and six common types(Thalictrum,Iridaceae,Potentilla,Ephedra,Brassicaceae,and Ulmus)have strong wind transport abilities;the estimated Relevant Source Area of Pollen(RSAP)is ca.1000 m when the sediment basin radius is set at 0.5 m.Ulmus,Artemisia,Brassicaceae,Chenopodiaceae,and Thalictrum have relative high RPPs;Poaceae,Cyperaceae,Potentilla,and Ephedra pollen have moderate RPPs;Asteraceae and Iridaceae have low RPPs.The reliability test of RPPs revealed that most of the RPPs are reliable in past vegetation reconstruction.However,the RPPs of Asteraceae and Iridaceae are obviously underestimated,and those of Poaceae,Chenopodiaceae,and Ephedra are either slightly underestimated or slightly overestimated,suggesting that those RPPs should be considered with caution.These RPPs were applied to estimating plant abundances for two fossil pollen spectra(from the Lake Bayanchagan and Lake Haoluku)covering the Holocene in typical steppe area,using the"Regional Estimates of Vegetation Abundance from Large Sites"(REVEALS)model.The RPPs-based vegetation reconstruction revealed that meadow-steppe dominated by Poaceae,Cyperaceae,and Artemisia plants flourished in this area before 6500–5600 cal yr BP,and then was replaced by present typical steppe.
基金National Natural Science Foundation of China,Grant/Award Numbers:11974303,12074332Qinglan Project of Jiangsu Province,Grant/Award Number:137050317the Interdisciplinary Research Project of Chemistry Discipline,Grant/Award Number:yzuxk202014 and High‐End Talent Program of Yangzhou University,Grant/Award Number:137080051。
文摘The key challenge of industrial water electrolysis is to design catalytic electrodes that can stabilize high current density with low power consumption(i.e.,overpotential),while industrial harsh conditions make the balance between electrode activity and stability more difficult.Here,we develop an efficient and durable electrode for water oxidation reaction(WOR),which yields a high current density of 1000 mA cm−2 at an overpotential of only 284 mV in 1M KOH at 25°C and shows robust stability even in 6M KOH strong alkali with an elevated temperature up to 80°C.This electrode is fabricated from a cheap nickel foam(NF)substrate through a simple one-step solution etching method,resulting in the growth of ultrafine phosphorus doped nickel-iron(oxy)hydroxide[P-(Ni,Fe)O_(x)H_(y)]nanoparticles embedded into abundant micropores on the surface,featured as a self-stabilized catalyst–substrate fusion electrode.Such self-stabilizing effect fastens highly active P-(Ni,Fe)O_(x)H_(y)species on conductive NF substrates with significant contribution to catalyst fixation and charge transfer,realizing a win–win tactics for WOR activity and durability at high current densities in harsh environments.This work affords a cost-effective WOR electrode that can well work at large current densities,suggestive of the rational design of catalyst electrodes toward industrial-scale water electrolysis.
文摘BACKGROUND The minimal clinically important difference(MCID)is defined as the smallest meaningful change in a health domain that a patient would identify as important.Thus,an improvement that exceeds the MCID can be used to define a successful treatment for the individual patient.AIM To quantify the rate of clinical improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis.METHODS Patients were treated with the Global Unite total shoulder platform arthroplasty between March 2017 and February 2019 at Herlev and Gentofte Hospital,Denmark.The patients were evaluated preoperatively and 3 months,6 months,12 months,and 24 months postoperatively using the Western Ontario Osteoarthritis of the Shoulder index(WOOS),Oxford Shoulder Score(OSS)and Constant-Murley Score(CMS).The rate of clinically relevant improvement was defined as the proportion of patients who had an improvement 24 months postoperatively that exceeded the MCID.Based on previous literature,MCID for WOOS,OSS,and CMS were defined as 12.3,4.3,and 12.8 respectively.RESULTS Forty-nine patients with a Global Unite total shoulder platform arthroplasty were included for the final analysis.Mean age at the time of surgery was 66 years(range 49.0-79.0,SD:8.3)and 65%were women.One patient was revised within the two years follow-up.The mean improvement from the preoperative assessment to the two-year follow-up was 46.1 points[95%confidence interval(95%CI):39.7-53.3,P<0.005]for WOOS,18.2 points(95%CI:15.5-21.0,P<0.005)for OSS and 37.8 points(95%CI:31.5-44.0,P<0.005)for CMS.Two years postoperatively,41 patients(87%)had an improvement in WOOS that exceeded the MCID,45 patients(94%)had an improvement in OSS that exceeded the MCID,and 42 patients(88%)had an improvement in CMS that exceeded the MCID.CONCLUSION Based on three shoulder-specific outcome measures we find that approximately 90%of patients has a clinically relevant improvement.This is a clear message when informing patients about their prognosis.
基金supported by Shenzhen Key Laboratory of Robotics Perception and Intelligence(ZDSYS20200810171800001)the Hong Kong RGC GRF(14200618)awarded to Max Q.-H.Meng.
文摘Sampling-based planning algorithm is a powerful tool for solving planning problems in highdimensional state spaces.In this article,we present a novel approach to sampling in the most promising regions,which significantly reduces planning time-consumption.The RRT#algorithm defines the Relevant Region based on the cost-to-come provided by the optimal forward-searching tree.However,it uses the cumulative cost of a direct connection between the current state and the goal state as the cost-to-go.To improve the path planning efficiency,we propose a batch sampling method that samples in a refined Relevant Region with a direct sampling strategy,which is defined according to the optimal cost-to-come and the adaptive cost-to-go,taking advantage of various sources of heuristic information.The proposed sampling approach allows the algorithm to build the search tree in the direction of the most promising area,resulting in a superior initial solution quality and reducing the overall computation time compared to related work.To validate the effectiveness of our method,we conducted several simulations in both SE(2)and SE(3)state spaces.And the simulation results demonstrate the superiorities of proposed algorithm.
文摘Objective： To investigate the clinical effects of electroacupuncture （EA） on the head points for improving gnosia in patients with vascular dementia （VD）. Methods： 90 VD patients were randomly divided into a drug group, an EA group and an EA plus drug group. Scoring with the M/VISE scale and detecting the relevant potentials were done before treatment and after a 6-week treatment. Results： Gnosia was improved after treatment in all the three groups with no significant difference by the intergroup comparison. Conclusion： The above three therapies can all improve gnosia, reduce the psychological stress, strengthen attention and shorten the awaiting time for recognition; and EA plus Nimodipine seems to be the best in the curative effect.
