This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,wher...This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.展开更多
Background: In 2012, U.S. health care providers wrote more than 259 million opioid prescriptions, which is twice as many as in 1998. Approximately 1 in 10 women report the use of opioids for pain management during pre...Background: In 2012, U.S. health care providers wrote more than 259 million opioid prescriptions, which is twice as many as in 1998. Approximately 1 in 10 women report the use of opioids for pain management during pregnancy. The Centers for Disease Control and Prevention (CDC) estimated that between 2008 and 2012, 39% of reproductive-aged women on Medicaid had filled a prescription for opioid medication each year, as did 28% of women with private insurance. The opioid epidemic extends to the state of New Jersey (NJ);however, limited data is available regarding opioid prescriptions among Medicaid and private insurance patients within the state. Objective: Evaluate opioid prescriptions filled in reproductive-aged women presenting in labor at a community teaching hospital in suburban New Jersey. Methods: We performed a retrospective cohort study using data obtained from patient records and the New Jersey Prescription Monitoring Program (NJPMP) database. We enrolled 200 patients that were admitted in labor between May 2015 and May 2016. Data was collected from reproductive-aged women during the one year preceding labor admission. We compared our findings to national data reported by the CDC using Chi-square analysis. Maternal demographic data were extracted from patient records and included age, insurance status (private insurance, Medicaid, and no insurance), race, and ethnicity. The primary outcome was opioid prescriptions filled. Results: Of the 200 women admitted in labor, 129 had private insurance, 63 had Medicaid, and 8 had no insurance. We found that 5.4% (7/129) of patients with private insurance, 4.8% (3/63) of patients with Medicaid, and 12.5% (1/8) of patients with no insurance filled opioid prescriptions. Overall, 5.5% (11/200) of women filled opioid prescriptions during the study period. Opioid prescriptions confirmed via NJPMP were significantly lower than rates reported by the CDC in Medicaid (4.8% vs. 41.4%, p-value 0.001) and private insurance (5.4% vs. 29.1%, p-value < 0.001) patients, respectively. Conclusion: Rates of opioid prescriptions filled were lower among our suburban cohort of women in New Jersey than national rates reported by the CDC. We did not confirm that patients with Medicaid filled more prescriptions than patients with private insurance. These discrepancies raise the question of whether a federal prescription monitoring program would better capture data than state-wide programs. Further research is needed to ensure that prescription monitoring programs are actually capturing accurate data.展开更多
The concern about the role of aerosols as to their effect in the Earth-Atmosphere system requires observation at multiple temporal and spatial scales. The Moderate Resolution Imaging Spectroradiameters （MODIS） is th...The concern about the role of aerosols as to their effect in the Earth-Atmosphere system requires observation at multiple temporal and spatial scales. The Moderate Resolution Imaging Spectroradiameters （MODIS） is the main aerosol optical depth （AOD） monitoring satellite instrument, and its accuracy and uncertainty need to be validated against ground based measurements routinely. The comparison between two ground AOD measurement programs, the United States Department of Agriculture （USDA） Ultmviolet-B Monitoring and Research Program （UVMRP） and the Aerosol Robotic Network （AERONET） program, confirms the consistency between them. The intercomparison between the MODIS AOD, the AERONET AOD, and the UVMRP AOD suggests that the UVMRP AOD measurements are suited to be an alternative ground-based validation source for satellite AOD products. The experiments show that the spatial-temporal dependency between the MODIS AOD and the UVMRP AOD is positive in the sense that the MODIS AOD compare more favorably with the UVMRP AOD as the spatial and temporal intervals are increased. However, the analysis shows that the optimal spatial interval for all time windows is defined by an angular subtense of around 1° to 1.25°, while the optimal time window is around 423 to 483 minutes at most spatial intervals. The spatial-temporal approach around 1.25° ＆ 423 minutes shows better agreement than the prevalent strategy of 0.25° ＆ 60 minutes found in other similar investigations.展开更多
Cement industrial emissions account for 32% of air pollution in Cambodia. With that in mind, we examined the environmental impact of Cambodia’s cement industry and identified ways that it could reduce air pollution. ...Cement industrial emissions account for 32% of air pollution in Cambodia. With that in mind, we examined the environmental impact of Cambodia’s cement industry and identified ways that it could reduce air pollution. The study focused on raw material extraction and preparation, calcination, and cement preparation. Data for the life-cycle inventory were provided by the Kampot Cement Plant. Air emissions were assessed using EMEP/EEA and IPCC criteria, and the impact assessment used ReCiPe (2016). The baseline analysis revealed that calcination contributed the most air pollutants, so mitigation scenarios focused on alternative fuels only during the calcination stage of cement production: 1) 100% coal (S1);2) 93% coal and 7% biomass (S2);3) 85% coal and 15% biomass (S3);4) 70% coal and 30% biomass (S4);and 5) 50% coal and 50% biomass (S5). The results demonstrated that certain mitigation measures reduced major emissions and environmental damage. S5 had the best results, reducing CO<sub>2</sub> by 49.97, NOx by 2.233, and SO<sub>2</sub> by 49.333%;however, it increased PM<sub>2.5</sub> by 19.60% and total heavy metal (Pb, Cd, Hg, As, Cr, Cu, Ni, Se, Zn) output by 28.113%. The results of the study showed reductions in serious health and environmental effects associated with climate change of 48.83%, ozone generation of 9.62%, and particulate matter formation of 28.80%. However, carcinogenic and non-carcinogenic human toxicity increased by 35.66%. Therefore, such mitigation effect would be benefit to carbon reduction target in Cambodia.展开更多
In the era of climate change,the visibility of environmental changes dictates public attention.Pictures of untamable bushfires,intense hurricanes,collapsing ice sheets are all gripping images that alarm us and urge us...In the era of climate change,the visibility of environmental changes dictates public attention.Pictures of untamable bushfires,intense hurricanes,collapsing ice sheets are all gripping images that alarm us and urge us to take action.The ocean,however,gives us less such visuals;the changes that are taking place there are often abstract and hidden.However,the environmental challenges in the ocean are less visible but no less grave;they come from multiple sources:pollution,plastic waste,ocean surface warming,ocean acidification(IPCC,2019).But the most direct and age-old impact we exert on the ocean and its ecosystems is overfishing(FAO,2018).展开更多
Hematological parameters can provide key information to an animal health status.However,this information is usually hard to obtain.Here,we described the hematological parameters of Leptodactylus podicipinus in the Bra...Hematological parameters can provide key information to an animal health status.However,this information is usually hard to obtain.Here,we described the hematological parameters of Leptodactylus podicipinus in the Brazilian Pantanal.We measured red blood cell morphometrics,erythrogram,and leukogram.We also tested for phylogenetic signal in the erythrogram and leukogram of 48 frog species from 15 families,testing if body size explains their variation.Lymphocytes were the most abundant leukocytes(>60%)in L.podicipinus,followed by neutrophils(∼10%).Given that L.podicipinus is an abundant and widely distributed species in central Brazil,knowing its hematological pattern can help establish a baseline and improve its use as a bioindicator of environmental degradation.Mean corpuscular hemoglobin and value contributed more to the phylomorphospace of erythrogram,in which Leptodactylus spp.and Hypsiboas raniceps had lower values of these variables,whereas Bufotes viridis and Hyla arborea had high values.The phylogenetic signal was spread throughout the dimensions of the leukogram phylomorphospace.The variables that most contributed to it were total leukocytes counts,lymphocytes,and neutrophils.We also found a moderate phylogenetic signal for both the erythrogram and leukogram.Accordingly,body size accounted for a low proportion of variation in both the leukogram(4.7%)and erythrogram(0.57%).By applying phylogenetic comparative methods to hematological parameters,our results add a new perspective on the evolution of blood cell physiology in frogs.展开更多
基金funded by the project of the China Geological Survey(DD20211364)the Science and Technology Talent Program of Ministry of Natural Resources of China(grant number 121106000000180039–2201)。
文摘This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.
文摘Background: In 2012, U.S. health care providers wrote more than 259 million opioid prescriptions, which is twice as many as in 1998. Approximately 1 in 10 women report the use of opioids for pain management during pregnancy. The Centers for Disease Control and Prevention (CDC) estimated that between 2008 and 2012, 39% of reproductive-aged women on Medicaid had filled a prescription for opioid medication each year, as did 28% of women with private insurance. The opioid epidemic extends to the state of New Jersey (NJ);however, limited data is available regarding opioid prescriptions among Medicaid and private insurance patients within the state. Objective: Evaluate opioid prescriptions filled in reproductive-aged women presenting in labor at a community teaching hospital in suburban New Jersey. Methods: We performed a retrospective cohort study using data obtained from patient records and the New Jersey Prescription Monitoring Program (NJPMP) database. We enrolled 200 patients that were admitted in labor between May 2015 and May 2016. Data was collected from reproductive-aged women during the one year preceding labor admission. We compared our findings to national data reported by the CDC using Chi-square analysis. Maternal demographic data were extracted from patient records and included age, insurance status (private insurance, Medicaid, and no insurance), race, and ethnicity. The primary outcome was opioid prescriptions filled. Results: Of the 200 women admitted in labor, 129 had private insurance, 63 had Medicaid, and 8 had no insurance. We found that 5.4% (7/129) of patients with private insurance, 4.8% (3/63) of patients with Medicaid, and 12.5% (1/8) of patients with no insurance filled opioid prescriptions. Overall, 5.5% (11/200) of women filled opioid prescriptions during the study period. Opioid prescriptions confirmed via NJPMP were significantly lower than rates reported by the CDC in Medicaid (4.8% vs. 41.4%, p-value 0.001) and private insurance (5.4% vs. 29.1%, p-value < 0.001) patients, respectively. Conclusion: Rates of opioid prescriptions filled were lower among our suburban cohort of women in New Jersey than national rates reported by the CDC. We did not confirm that patients with Medicaid filled more prescriptions than patients with private insurance. These discrepancies raise the question of whether a federal prescription monitoring program would better capture data than state-wide programs. Further research is needed to ensure that prescription monitoring programs are actually capturing accurate data.
文摘The concern about the role of aerosols as to their effect in the Earth-Atmosphere system requires observation at multiple temporal and spatial scales. The Moderate Resolution Imaging Spectroradiameters （MODIS） is the main aerosol optical depth （AOD） monitoring satellite instrument, and its accuracy and uncertainty need to be validated against ground based measurements routinely. The comparison between two ground AOD measurement programs, the United States Department of Agriculture （USDA） Ultmviolet-B Monitoring and Research Program （UVMRP） and the Aerosol Robotic Network （AERONET） program, confirms the consistency between them. The intercomparison between the MODIS AOD, the AERONET AOD, and the UVMRP AOD suggests that the UVMRP AOD measurements are suited to be an alternative ground-based validation source for satellite AOD products. The experiments show that the spatial-temporal dependency between the MODIS AOD and the UVMRP AOD is positive in the sense that the MODIS AOD compare more favorably with the UVMRP AOD as the spatial and temporal intervals are increased. However, the analysis shows that the optimal spatial interval for all time windows is defined by an angular subtense of around 1° to 1.25°, while the optimal time window is around 423 to 483 minutes at most spatial intervals. The spatial-temporal approach around 1.25° ＆ 423 minutes shows better agreement than the prevalent strategy of 0.25° ＆ 60 minutes found in other similar investigations.
文摘Cement industrial emissions account for 32% of air pollution in Cambodia. With that in mind, we examined the environmental impact of Cambodia’s cement industry and identified ways that it could reduce air pollution. The study focused on raw material extraction and preparation, calcination, and cement preparation. Data for the life-cycle inventory were provided by the Kampot Cement Plant. Air emissions were assessed using EMEP/EEA and IPCC criteria, and the impact assessment used ReCiPe (2016). The baseline analysis revealed that calcination contributed the most air pollutants, so mitigation scenarios focused on alternative fuels only during the calcination stage of cement production: 1) 100% coal (S1);2) 93% coal and 7% biomass (S2);3) 85% coal and 15% biomass (S3);4) 70% coal and 30% biomass (S4);and 5) 50% coal and 50% biomass (S5). The results demonstrated that certain mitigation measures reduced major emissions and environmental damage. S5 had the best results, reducing CO<sub>2</sub> by 49.97, NOx by 2.233, and SO<sub>2</sub> by 49.333%;however, it increased PM<sub>2.5</sub> by 19.60% and total heavy metal (Pb, Cd, Hg, As, Cr, Cu, Ni, Se, Zn) output by 28.113%. The results of the study showed reductions in serious health and environmental effects associated with climate change of 48.83%, ozone generation of 9.62%, and particulate matter formation of 28.80%. However, carcinogenic and non-carcinogenic human toxicity increased by 35.66%. Therefore, such mitigation effect would be benefit to carbon reduction target in Cambodia.
文摘In the era of climate change,the visibility of environmental changes dictates public attention.Pictures of untamable bushfires,intense hurricanes,collapsing ice sheets are all gripping images that alarm us and urge us to take action.The ocean,however,gives us less such visuals;the changes that are taking place there are often abstract and hidden.However,the environmental challenges in the ocean are less visible but no less grave;they come from multiple sources:pollution,plastic waste,ocean surface warming,ocean acidification(IPCC,2019).But the most direct and age-old impact we exert on the ocean and its ecosystems is overfishing(FAO,2018).
基金SISBIO provided collecting permit(#63297-1)This study was funded in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil(CAPES)–Finance Code 001.CESF received a grant from the Fundação de Apoio ao Desenvolvimento do Ensino,Ciência e Tecnologia do Estado de Mato Grosso do Sul(#71/700.136)+1 种基金has been continuously supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico(grant#310058/2020-1)C.O.has been continuously supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico(grant#304552/2019-4).
文摘Hematological parameters can provide key information to an animal health status.However,this information is usually hard to obtain.Here,we described the hematological parameters of Leptodactylus podicipinus in the Brazilian Pantanal.We measured red blood cell morphometrics,erythrogram,and leukogram.We also tested for phylogenetic signal in the erythrogram and leukogram of 48 frog species from 15 families,testing if body size explains their variation.Lymphocytes were the most abundant leukocytes(>60%)in L.podicipinus,followed by neutrophils(∼10%).Given that L.podicipinus is an abundant and widely distributed species in central Brazil,knowing its hematological pattern can help establish a baseline and improve its use as a bioindicator of environmental degradation.Mean corpuscular hemoglobin and value contributed more to the phylomorphospace of erythrogram,in which Leptodactylus spp.and Hypsiboas raniceps had lower values of these variables,whereas Bufotes viridis and Hyla arborea had high values.The phylogenetic signal was spread throughout the dimensions of the leukogram phylomorphospace.The variables that most contributed to it were total leukocytes counts,lymphocytes,and neutrophils.We also found a moderate phylogenetic signal for both the erythrogram and leukogram.Accordingly,body size accounted for a low proportion of variation in both the leukogram(4.7%)and erythrogram(0.57%).By applying phylogenetic comparative methods to hematological parameters,our results add a new perspective on the evolution of blood cell physiology in frogs.
