Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also i...Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.展开更多
BACKGROUND:Neuroendocrine dysfunction after traumatic brain injury(TBI)has received increased attention due to its impact on the recovery of neural function.The purpose of this study is to investigate the incidence an...BACKGROUND:Neuroendocrine dysfunction after traumatic brain injury(TBI)has received increased attention due to its impact on the recovery of neural function.The purpose of this study is to investigate the incidence and risk factors of adrenocortical insuffi ciency(AI)after TBI to reveal independent predictors and build a prediction model of AI after TBI.METHODS:Enrolled patients were grouped into the AI and non-AI groups.Fourteen preset impact factors were recorded.Patients were regrouped according to each impact factor as a categorical variable.Univariate and multiple logistic regression analyses were performed to screen the related independent risk factors of AI after TBI and develop the predictive model.RESULTS:A total of 108 patients were recruited,of whom 34(31.5%)patients had AI.Nine factors(age,Glasgow Coma Scale[GCS]score on admission,mean arterial pressure[MAP],urinary volume,serum sodium level,cerebral hernia,frontal lobe contusion,diff use axonal injury[DAI],and skull base fracture)were probably related to AI after TBI.Three factors(urinary volume[X4],serum sodium level[X5],and DAI[X8])were independent variables,based on which a prediction model was developed(logit P=-3.552+2.583X4+2.235X5+2.269X8).CONCLUSIONS:The incidence of AI after TBI is high.Factors such as age,GCS score,MAP,urinary volume,serum sodium level,cerebral hernia,frontal lobe contusion,DAI,and skull base fracture are probably related to AI after TBI.Urinary volume,serum sodium level,and DAI are the independent predictors of AI after TBI.展开更多
BACKGROUND: The present study aimed to determine the short-term and long-term outcomes of critically ill patients with acute respiratory insuffi ciency who had received sedation or no sedation.METHODS: The data of 91 ...BACKGROUND: The present study aimed to determine the short-term and long-term outcomes of critically ill patients with acute respiratory insuffi ciency who had received sedation or no sedation.METHODS: The data of 91 patients who had received mechanical ventilation in the first 24 hours between November 2008 and October 2009 were retrospectively analyzed. These patients were divided into two groups: a sedation group(n=28) and a non-sedation group(n=63). The patients were also grouped in two groups: deep sedation group and daily interruption and /or light sedation group.RESULTS: Overall, the 91 patients who had received ventilation ≥48 hours were analyzed. Multivariate analysis demonstrated two independent risk factors for in-hospital death: sequential organ failure assessment score(P=0.019, RR 1.355, 95%CI 1.051–1.747, B=0.304, SE=0.130, Wald=50483) and sedation(P=0.041, RR 5.015, 95%CI 1.072–23.459, B=1.612, SE=0.787, Wald=4.195). Compared with the patients who had received no sedation, those who had received sedation had a longer duration of ventilation, a longer stay in intensive care unit and hospital, and an increased in-hospital mortality rate. The Kaplan-Meier method showed that patients who had received sedation had a lower 60-month survival rate than those who had received no sedation(76.7% vs. 88.9%, Log-rank test=3.630, P=0.057). Compared with the patients who had received deep sedation, those who had received daily interruption or light sedation showed a decreased in-hospital mortality rate(57.1% vs. 9.5%, P=0.008). The 60-month survival of the patients who had received deep sedation was signifi cantly lower than that of those who had daily interruption or light sedation(38.1% vs. 90.5%, Log-rank test=6.783, P=0.009).CONCLUSIONS: Sedation was associated with in-hospital death. The patients who had received sedation had a longer duration of ventilation, a longer stay in intensive care unit and in hospital, and an increased in-hospital mortality rate compared with the patients who did not receive sedation. Compared with daily interruption or light sedation, deep sedation increased the in-hospital mortality and decreased the 60-month survival for patients who had received sedation.展开更多
In human immunodef iciency virus(HIV)-infected people kidney disease is as an important cause of morbidity and mortality. Clinical features of kidney damage in HIV-infected patients range from asymptomatic microalbumi...In human immunodef iciency virus(HIV)-infected people kidney disease is as an important cause of morbidity and mortality. Clinical features of kidney damage in HIV-infected patients range from asymptomatic microalbuminuria to nephrotic syndrome. The lack of specif ic clinical features despite the presence of heavy proteinuria may mask the renal involvement. Indeed, it is important in HIV patients to monitor renal function to early discover a possible kidney injury. After the introduction of antiretroviral therapy, mortality and morbidity associated to HIV-infection have shown a substantial reduction, although a variety of side effects for longterm use of highly active antiretroviral therapy, including renal toxicity, has emerged. Among more than 20 currently available antiretroviral agents, many of them can occasionally cause reversible or irreversible nephrotoxicity. At now, three antiretroviral agents, i.e., indinavir, atazanavir and tenofovir disoproxil fumarate have a well established association with direct nephrotoxicity. This review focuses on major causes of proteinuria and other pathological f indings related to kidney disease in HIV-infected children and adolescents.展开更多
This study seeks to evaluate the comparative productivity of 32 listed tourism companies which are the main suppliers of China tourism, using the popular methodology known as the data envelopment analysis(DEA). This s...This study seeks to evaluate the comparative productivity of 32 listed tourism companies which are the main suppliers of China tourism, using the popular methodology known as the data envelopment analysis(DEA). This study analyzes the productivity of listed tourism companies from business and region aspects based on the calculation of Malmquist index. The results show that(1) the overall productivity is non-effi cient(0.954);(2) the productivity of accommodation and catering is biggest, which shows the tourism develops quickly with supports from technology;(3) the productivity in western China is highest, where the economy and tourism attraction are better than other regions; and(4) the effi ciency differences among the listed tourism companies are not signifi cant, and they attribute to the scale effi-ciency, that is the input of the fi nance, resource, talents and policy.展开更多
Prediction of the nutrient deficiency range and control of it through application of an appropriate amount of fertiliser at all growth stages is critical to achieving a qualitative and quantitative yield.Distributing f...Prediction of the nutrient deficiency range and control of it through application of an appropriate amount of fertiliser at all growth stages is critical to achieving a qualitative and quantitative yield.Distributing fertiliser in optimum amounts will protect the environment’s condition and human health risks.Early identification also prevents the disease’s occurrence in groundnut crops.A convo-lutional neural network is a computer vision algorithm that can be replaced in the place of human experts and laboratory methods to predict groundnut crop nitro-gen nutrient deficiency through image features.Since chlorophyll and nitrogen are proportionate to one another,the Smart Nutrient Deficiency Prediction System(SNDP)is proposed to detect and categorise the chlorophyll concentration range via which nitrogen concentration can be known.The model’sfirst part is to per-form preprocessing using Groundnut Leaf Image Preprocessing(GLIP).Then,in the second part,feature extraction using a convolution process with Non-negative ReLU(CNNR)is done,and then,in the third part,the extracted features areflat-tened and given to the dense layer(DL)layer.Next,the Maximum Margin clas-sifier(MMC)is deployed and takes the input from DL for the classification process tofind CCR.The dataset used in this work has no visible symptoms of a deficiency with three categories:low level(LL),beginning stage of low level(BSLL),and appropriate level(AL).This model could help to predict nitrogen deficiency before perceivable symptoms.The performance of the implemented model is analysed and compared with ImageNet pre-trained models.The result shows that the CNNR-MMC model obtained the highest training and validation accuracy of 99%and 95%,respectively,compared to existing pre-trained models.展开更多
Based on the Data Envelopment Analysis method,and by using CCR and BCC model,Super Efficiency model and Malmquist model guided by input efficiency,the input-output efficiency of elements of urban construction land in ...Based on the Data Envelopment Analysis method,and by using CCR and BCC model,Super Efficiency model and Malmquist model guided by input efficiency,the input-output efficiency of elements of urban construction land in different jurisdictions of Beijing from 2005 to 2015 was studied.The results showed that there were obvious differences between input-output efficiency of elements of urban construction land in different jurisdictions of Beijing,among which the efficiency of the core area of capital,Yanqing District,Fangshan District and Huairou District was relatively high,while the efficiency of Daxing District,Fengtai District and Miyun District was relatively low.There was no obvious correlation between efficiency differentiation and location factors,which is mainly caused by whether the land use in each jurisdiction has scale effect,whether the technology is improved,whether the input is redundant and whether the output is insufficient.For the jurisdiction of inefficient land use,we should strengthen the consciousness of intensive land use,improve the technical level,appropriately reduce the redundancy of input elements,and pay attention to the output of social and ecological benefits.展开更多
文摘Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.
基金a grant from the National Clinical Specialty Construction Project of China(2013-544).
文摘BACKGROUND:Neuroendocrine dysfunction after traumatic brain injury(TBI)has received increased attention due to its impact on the recovery of neural function.The purpose of this study is to investigate the incidence and risk factors of adrenocortical insuffi ciency(AI)after TBI to reveal independent predictors and build a prediction model of AI after TBI.METHODS:Enrolled patients were grouped into the AI and non-AI groups.Fourteen preset impact factors were recorded.Patients were regrouped according to each impact factor as a categorical variable.Univariate and multiple logistic regression analyses were performed to screen the related independent risk factors of AI after TBI and develop the predictive model.RESULTS:A total of 108 patients were recruited,of whom 34(31.5%)patients had AI.Nine factors(age,Glasgow Coma Scale[GCS]score on admission,mean arterial pressure[MAP],urinary volume,serum sodium level,cerebral hernia,frontal lobe contusion,diff use axonal injury[DAI],and skull base fracture)were probably related to AI after TBI.Three factors(urinary volume[X4],serum sodium level[X5],and DAI[X8])were independent variables,based on which a prediction model was developed(logit P=-3.552+2.583X4+2.235X5+2.269X8).CONCLUSIONS:The incidence of AI after TBI is high.Factors such as age,GCS score,MAP,urinary volume,serum sodium level,cerebral hernia,frontal lobe contusion,DAI,and skull base fracture are probably related to AI after TBI.Urinary volume,serum sodium level,and DAI are the independent predictors of AI after TBI.
文摘BACKGROUND: The present study aimed to determine the short-term and long-term outcomes of critically ill patients with acute respiratory insuffi ciency who had received sedation or no sedation.METHODS: The data of 91 patients who had received mechanical ventilation in the first 24 hours between November 2008 and October 2009 were retrospectively analyzed. These patients were divided into two groups: a sedation group(n=28) and a non-sedation group(n=63). The patients were also grouped in two groups: deep sedation group and daily interruption and /or light sedation group.RESULTS: Overall, the 91 patients who had received ventilation ≥48 hours were analyzed. Multivariate analysis demonstrated two independent risk factors for in-hospital death: sequential organ failure assessment score(P=0.019, RR 1.355, 95%CI 1.051–1.747, B=0.304, SE=0.130, Wald=50483) and sedation(P=0.041, RR 5.015, 95%CI 1.072–23.459, B=1.612, SE=0.787, Wald=4.195). Compared with the patients who had received no sedation, those who had received sedation had a longer duration of ventilation, a longer stay in intensive care unit and hospital, and an increased in-hospital mortality rate. The Kaplan-Meier method showed that patients who had received sedation had a lower 60-month survival rate than those who had received no sedation(76.7% vs. 88.9%, Log-rank test=3.630, P=0.057). Compared with the patients who had received deep sedation, those who had received daily interruption or light sedation showed a decreased in-hospital mortality rate(57.1% vs. 9.5%, P=0.008). The 60-month survival of the patients who had received deep sedation was signifi cantly lower than that of those who had daily interruption or light sedation(38.1% vs. 90.5%, Log-rank test=6.783, P=0.009).CONCLUSIONS: Sedation was associated with in-hospital death. The patients who had received sedation had a longer duration of ventilation, a longer stay in intensive care unit and in hospital, and an increased in-hospital mortality rate compared with the patients who did not receive sedation. Compared with daily interruption or light sedation, deep sedation increased the in-hospital mortality and decreased the 60-month survival for patients who had received sedation.
文摘In human immunodef iciency virus(HIV)-infected people kidney disease is as an important cause of morbidity and mortality. Clinical features of kidney damage in HIV-infected patients range from asymptomatic microalbuminuria to nephrotic syndrome. The lack of specif ic clinical features despite the presence of heavy proteinuria may mask the renal involvement. Indeed, it is important in HIV patients to monitor renal function to early discover a possible kidney injury. After the introduction of antiretroviral therapy, mortality and morbidity associated to HIV-infection have shown a substantial reduction, although a variety of side effects for longterm use of highly active antiretroviral therapy, including renal toxicity, has emerged. Among more than 20 currently available antiretroviral agents, many of them can occasionally cause reversible or irreversible nephrotoxicity. At now, three antiretroviral agents, i.e., indinavir, atazanavir and tenofovir disoproxil fumarate have a well established association with direct nephrotoxicity. This review focuses on major causes of proteinuria and other pathological f indings related to kidney disease in HIV-infected children and adolescents.
基金supported by the project of Shaanxi Normal University(Grant No.999521)Xianyang Normal University(Grant Nos.11XSYK316,201002001)
文摘This study seeks to evaluate the comparative productivity of 32 listed tourism companies which are the main suppliers of China tourism, using the popular methodology known as the data envelopment analysis(DEA). This study analyzes the productivity of listed tourism companies from business and region aspects based on the calculation of Malmquist index. The results show that(1) the overall productivity is non-effi cient(0.954);(2) the productivity of accommodation and catering is biggest, which shows the tourism develops quickly with supports from technology;(3) the productivity in western China is highest, where the economy and tourism attraction are better than other regions; and(4) the effi ciency differences among the listed tourism companies are not signifi cant, and they attribute to the scale effi-ciency, that is the input of the fi nance, resource, talents and policy.
文摘Prediction of the nutrient deficiency range and control of it through application of an appropriate amount of fertiliser at all growth stages is critical to achieving a qualitative and quantitative yield.Distributing fertiliser in optimum amounts will protect the environment’s condition and human health risks.Early identification also prevents the disease’s occurrence in groundnut crops.A convo-lutional neural network is a computer vision algorithm that can be replaced in the place of human experts and laboratory methods to predict groundnut crop nitro-gen nutrient deficiency through image features.Since chlorophyll and nitrogen are proportionate to one another,the Smart Nutrient Deficiency Prediction System(SNDP)is proposed to detect and categorise the chlorophyll concentration range via which nitrogen concentration can be known.The model’sfirst part is to per-form preprocessing using Groundnut Leaf Image Preprocessing(GLIP).Then,in the second part,feature extraction using a convolution process with Non-negative ReLU(CNNR)is done,and then,in the third part,the extracted features areflat-tened and given to the dense layer(DL)layer.Next,the Maximum Margin clas-sifier(MMC)is deployed and takes the input from DL for the classification process tofind CCR.The dataset used in this work has no visible symptoms of a deficiency with three categories:low level(LL),beginning stage of low level(BSLL),and appropriate level(AL).This model could help to predict nitrogen deficiency before perceivable symptoms.The performance of the implemented model is analysed and compared with ImageNet pre-trained models.The result shows that the CNNR-MMC model obtained the highest training and validation accuracy of 99%and 95%,respectively,compared to existing pre-trained models.
文摘Based on the Data Envelopment Analysis method,and by using CCR and BCC model,Super Efficiency model and Malmquist model guided by input efficiency,the input-output efficiency of elements of urban construction land in different jurisdictions of Beijing from 2005 to 2015 was studied.The results showed that there were obvious differences between input-output efficiency of elements of urban construction land in different jurisdictions of Beijing,among which the efficiency of the core area of capital,Yanqing District,Fangshan District and Huairou District was relatively high,while the efficiency of Daxing District,Fengtai District and Miyun District was relatively low.There was no obvious correlation between efficiency differentiation and location factors,which is mainly caused by whether the land use in each jurisdiction has scale effect,whether the technology is improved,whether the input is redundant and whether the output is insufficient.For the jurisdiction of inefficient land use,we should strengthen the consciousness of intensive land use,improve the technical level,appropriately reduce the redundancy of input elements,and pay attention to the output of social and ecological benefits.
