Secondary water supply systems(SWSSs)are important components of the water supply infrastructure that ensure residents’drinking water safety.SWSSs are characterized by long detention time,warm temperature,and unreaso...Secondary water supply systems(SWSSs)are important components of the water supply infrastructure that ensure residents’drinking water safety.SWSSs are characterized by long detention time,warm temperature,and unreasonable management,which may trigger the deterioration of water quality and increase risks.In this study,drinking water quality index(DWQI)and health risk assessment(HRA)were selected and modified to quantitatively assess the water quality and health risks of SWSSs in residential neighborhoods.In total,121 seasonal water samples were selected.It was observed that the water quality was excellent with the DWQI of 0.14±0.04,excluding one sample,which was extremely poor owing to its excessive total bacterial count.The HRA results revealed that the health risks were low:negligible non-carcinogenic risk for any population;negligible and acceptable carcinogenic risk for children aged 6–17 and adults.However,samples revealed higher carcinogenic risk(7.63×10−5±3.29×10−6)for children aged 0–5,and arsenic was the major substance.Summer samples had poor water quality and higher health risks,which called for attention.To further investigate the water quality and health risks of SWSSs,monthly sampling was conducted during summer.All 24 water samples were qualified in Chinese standard(GB 5749-2022)and characterized as excellent quality.Their HRA results were consistent with the seasonal samples’and the health risks were mainly concentrated in May.Overall,our study provides a suitable framework for water quality security,advice for managers,and references for administrators in other cities.展开更多
Data imputation is an essential pre-processing task for data governance,aimed at filling in incomplete data.However,conventional data imputation methods can only partly alleviate data incompleteness using isolated tab...Data imputation is an essential pre-processing task for data governance,aimed at filling in incomplete data.However,conventional data imputation methods can only partly alleviate data incompleteness using isolated tabular data,and they fail to achieve the best balance between accuracy and eficiency.In this paper,we present a novel visual analysis approach for data imputation.We develop a multi-party tabular data association strategy that uses intelligent algorithms to identify similar columns and establish column correlations across multiple tables.Then,we perform the initial imputation of incomplete data using correlated data entries from other tables.Additionally,we develop a visual analysis system to refine data imputation candidates.Our interactive system combines the multi-party data imputation approach with expert knowledge,allowing for a better understanding of the relational structure of the data.This significantly enhances the accuracy and eficiency of data imputation,thereby enhancing the quality of data governance and the intrinsic value of data assets.Experimental validation and user surveys demonstrate that this method supports users in verifying and judging the associated columns and similar rows using theirdomain knowledge.展开更多
Visualization and artificial intelligence(AI)are well-applied approaches to data analysis.On one hand,visualization can facilitate humans in data understanding through intuitive visual representation and interactive e...Visualization and artificial intelligence(AI)are well-applied approaches to data analysis.On one hand,visualization can facilitate humans in data understanding through intuitive visual representation and interactive exploration.On the other hand,AI is able to learn from data and implement bulky tasks for humans.In complex data analysis scenarios,like epidemic traceability and city planning,humans need to understand large-scale data and make decisions,which requires complementing the strengths of both visualization and AI.Existing studies have introduced AI-assisted visualization as AI4VIS and visualization-assisted AI as VIS4AI.However,how can AI and visualization complement each other and be integrated into data analysis processes are still missing.In this paper,we define three integration levels of visualization and AI.The highest integration level is described as the framework of VIS+AI,which allows AI to learn human intelligence from interactions and communicate with humans through visual interfaces.We also summarize future directions of VIS+AI to inspire related studies.展开更多
Background:Promoting wound healing is crucial to restore the vital barrier function of injured skin.Growth factor products including epidermal growth factor(EGF),fibroblast growth factor(FGF)and granulocyte-macrophage...Background:Promoting wound healing is crucial to restore the vital barrier function of injured skin.Growth factor products including epidermal growth factor(EGF),fibroblast growth factor(FGF)and granulocyte-macrophage colony stimulating factor(GM-CSF)have been used for decades although no systematic evaluation exists regarding their effectiveness and safety issues in treating acute skin wounds.This has resulted in a lack of guidelines and standards for proper application regimes.Therefore,this systematic review and meta-analysis was performed to critically evaluate the effectiveness and safety of these growth factors on skin acute wounds and provide guidelines for application regimes.Methods:We searched PubMed/Medline(1980-2020),Cochrane Library(1980-2020),Cochrane CENTRAL(from establishment to 2020),ClinicalTrials.gov(from establishment to 2020),Chinese Journal Full-text Database(CNKI,1994-2020),China Biology Medicine disc(CBM,1978-2019),Chinese Scientific Journal Database(VIP,1989-2020)andWanfang Database(WFDATA,1980-2019).Randomized controlled trials(RCTs),quasi-RCTs and controlled clinical trials treating patients with acute skin wounds from various causes and with those available growth factors were included.Results:A total of 7573 papers were identified through database searching;229 papers including 281 studies were kept after final screening.Administering growth factors significantly short-ened the healing time of acute skin wounds,including superficial burn injuries[mean differ-ence(MD)=−3.02;95%confidence interval(CI):−3.31∼−2.74;p<0.00001],deep burn injuries(MD=−5.63;95%CI:−7.10∼−4.17;p<0.00001),traumata and surgical wounds(MD=−4.50;95%CI:−5.55∼−3.44;p<0.00001).Growth factors increased the healing rate of acute skin wounds and decreased scar scores.The incidence of adverse reactions was lower in the growth factor treatment group than in the non-growth factor group.Conclusions:The studied growth factors not only are effective and safe for managing acute skin wounds,but also accelerate their healing with no severe adverse reactions.展开更多
The accurate and objective evaluation of burn depth is a significant challenge in burn wound care.Herein,we used near infrared spectroscopy(NIRS)technology to measure the different depth of thermal burns in ex vivo po...The accurate and objective evaluation of burn depth is a significant challenge in burn wound care.Herein,we used near infrared spectroscopy(NIRS)technology to measure the different depth of thermal burns in ex vivo porcine models.Based on the intensity of the spectral signals and the diffuse reflection theory,we extracted the optical parameters involved in functional(total hemoglobin andwater content)and structural(tissue scattered size and scattered particles)features that reflect the changes in burn depth.Next,we applied support vector regression to construct a model including the optical property parameters and the burn depth.Finally,we histologically verified the burn depth data collected via NIRS.The results showed that our inversion model could achieve an average relative error of about 7.63%,while the NIRS technology diagnostic accuracy was in the range of 50μm.For the first time,this novel technique provides physicians with real-time burn depth information objectively and accurately.展开更多
基金supported by the National Natural Science Foundation of China(No.U2005206)the Xiamen Municipal Bureau of Science and Technology(China)(No.YDZX20203502000003).
文摘Secondary water supply systems(SWSSs)are important components of the water supply infrastructure that ensure residents’drinking water safety.SWSSs are characterized by long detention time,warm temperature,and unreasonable management,which may trigger the deterioration of water quality and increase risks.In this study,drinking water quality index(DWQI)and health risk assessment(HRA)were selected and modified to quantitatively assess the water quality and health risks of SWSSs in residential neighborhoods.In total,121 seasonal water samples were selected.It was observed that the water quality was excellent with the DWQI of 0.14±0.04,excluding one sample,which was extremely poor owing to its excessive total bacterial count.The HRA results revealed that the health risks were low:negligible non-carcinogenic risk for any population;negligible and acceptable carcinogenic risk for children aged 6–17 and adults.However,samples revealed higher carcinogenic risk(7.63×10−5±3.29×10−6)for children aged 0–5,and arsenic was the major substance.Summer samples had poor water quality and higher health risks,which called for attention.To further investigate the water quality and health risks of SWSSs,monthly sampling was conducted during summer.All 24 water samples were qualified in Chinese standard(GB 5749-2022)and characterized as excellent quality.Their HRA results were consistent with the seasonal samples’and the health risks were mainly concentrated in May.Overall,our study provides a suitable framework for water quality security,advice for managers,and references for administrators in other cities.
基金Project supported by the Key R&D"Pioneer"Tackling Plan Program of Zhejiang Province,China(No.2023C01119)the"Ten Thousand Talents Plan"Science and Technology Innovation Leading Talent Program of Zhejiang Province,China(No.2022R52044)+1 种基金the Major Standardization Pilot Projects for the Digital Economy(Digital Trade Sector)of Zhejiang Province,China(No.SJ-Bz/2023053)the National Natural Science Foundationof China(No.62132017)。
文摘Data imputation is an essential pre-processing task for data governance,aimed at filling in incomplete data.However,conventional data imputation methods can only partly alleviate data incompleteness using isolated tabular data,and they fail to achieve the best balance between accuracy and eficiency.In this paper,we present a novel visual analysis approach for data imputation.We develop a multi-party tabular data association strategy that uses intelligent algorithms to identify similar columns and establish column correlations across multiple tables.Then,we perform the initial imputation of incomplete data using correlated data entries from other tables.Additionally,we develop a visual analysis system to refine data imputation candidates.Our interactive system combines the multi-party data imputation approach with expert knowledge,allowing for a better understanding of the relational structure of the data.This significantly enhances the accuracy and eficiency of data imputation,thereby enhancing the quality of data governance and the intrinsic value of data assets.Experimental validation and user surveys demonstrate that this method supports users in verifying and judging the associated columns and similar rows using theirdomain knowledge.
基金supported by the National Natural Science Foundation of China(Grant Nos.62202244,62132017,and 62036010).
文摘Visualization and artificial intelligence(AI)are well-applied approaches to data analysis.On one hand,visualization can facilitate humans in data understanding through intuitive visual representation and interactive exploration.On the other hand,AI is able to learn from data and implement bulky tasks for humans.In complex data analysis scenarios,like epidemic traceability and city planning,humans need to understand large-scale data and make decisions,which requires complementing the strengths of both visualization and AI.Existing studies have introduced AI-assisted visualization as AI4VIS and visualization-assisted AI as VIS4AI.However,how can AI and visualization complement each other and be integrated into data analysis processes are still missing.In this paper,we define three integration levels of visualization and AI.The highest integration level is described as the framework of VIS+AI,which allows AI to learn human intelligence from interactions and communicate with humans through visual interfaces.We also summarize future directions of VIS+AI to inspire related studies.
文摘Background:Promoting wound healing is crucial to restore the vital barrier function of injured skin.Growth factor products including epidermal growth factor(EGF),fibroblast growth factor(FGF)and granulocyte-macrophage colony stimulating factor(GM-CSF)have been used for decades although no systematic evaluation exists regarding their effectiveness and safety issues in treating acute skin wounds.This has resulted in a lack of guidelines and standards for proper application regimes.Therefore,this systematic review and meta-analysis was performed to critically evaluate the effectiveness and safety of these growth factors on skin acute wounds and provide guidelines for application regimes.Methods:We searched PubMed/Medline(1980-2020),Cochrane Library(1980-2020),Cochrane CENTRAL(from establishment to 2020),ClinicalTrials.gov(from establishment to 2020),Chinese Journal Full-text Database(CNKI,1994-2020),China Biology Medicine disc(CBM,1978-2019),Chinese Scientific Journal Database(VIP,1989-2020)andWanfang Database(WFDATA,1980-2019).Randomized controlled trials(RCTs),quasi-RCTs and controlled clinical trials treating patients with acute skin wounds from various causes and with those available growth factors were included.Results:A total of 7573 papers were identified through database searching;229 papers including 281 studies were kept after final screening.Administering growth factors significantly short-ened the healing time of acute skin wounds,including superficial burn injuries[mean differ-ence(MD)=−3.02;95%confidence interval(CI):−3.31∼−2.74;p<0.00001],deep burn injuries(MD=−5.63;95%CI:−7.10∼−4.17;p<0.00001),traumata and surgical wounds(MD=−4.50;95%CI:−5.55∼−3.44;p<0.00001).Growth factors increased the healing rate of acute skin wounds and decreased scar scores.The incidence of adverse reactions was lower in the growth factor treatment group than in the non-growth factor group.Conclusions:The studied growth factors not only are effective and safe for managing acute skin wounds,but also accelerate their healing with no severe adverse reactions.
基金supported by grants from the National Natural Science Foundation of China(No.81701904).
文摘The accurate and objective evaluation of burn depth is a significant challenge in burn wound care.Herein,we used near infrared spectroscopy(NIRS)technology to measure the different depth of thermal burns in ex vivo porcine models.Based on the intensity of the spectral signals and the diffuse reflection theory,we extracted the optical parameters involved in functional(total hemoglobin andwater content)and structural(tissue scattered size and scattered particles)features that reflect the changes in burn depth.Next,we applied support vector regression to construct a model including the optical property parameters and the burn depth.Finally,we histologically verified the burn depth data collected via NIRS.The results showed that our inversion model could achieve an average relative error of about 7.63%,while the NIRS technology diagnostic accuracy was in the range of 50μm.For the first time,this novel technique provides physicians with real-time burn depth information objectively and accurately.
