This study demonstrates the complexity and importance of water quality as a measure of the health and sustainability of ecosystems that directly influence biodiversity,human health,and the world economy.The predictabi...This study demonstrates the complexity and importance of water quality as a measure of the health and sustainability of ecosystems that directly influence biodiversity,human health,and the world economy.The predictability of water quality thus plays a crucial role in managing our ecosystems to make informed decisions and,hence,proper environmental management.This study addresses these challenges by proposing an effective machine learning methodology applied to the“Water Quality”public dataset.The methodology has modeled the dataset suitable for providing prediction classification analysis with high values of the evaluating parameters such as accuracy,sensitivity,and specificity.The proposed methodology is based on two novel approaches:(a)the SMOTE method to deal with unbalanced data and(b)the skillfully involved classical machine learning models.This paper uses Random Forests,Decision Trees,XGBoost,and Support Vector Machines because they can handle large datasets,train models for handling skewed datasets,and provide high accuracy in water quality classification.A key contribution of this work is the use of custom sampling strategies within the SMOTE approach,which significantly enhanced performance metrics and improved class imbalance handling.The results demonstrate significant improvements in predictive performance,achieving the highest reported metrics:accuracy(98.92%vs.96.06%),sensitivity(98.3%vs.71.26%),and F1 score(98.37%vs.79.74%)using the XGBoost model.These improvements underscore the effectiveness of our custom SMOTE sampling strategies in addressing class imbalance.The findings contribute to environmental management by enabling ecology specialists to develop more accurate strategies for monitoring,assessing,and managing drinking water quality,ensuring better ecosystem and public health outcomes.展开更多
The utilization of pure hydrogen as an energy source in fuel cells gave rise to renewed interest in developing active and stable water-gas shift catalysts. Gold catalysts have proven to be very efficient for water-gas...The utilization of pure hydrogen as an energy source in fuel cells gave rise to renewed interest in developing active and stable water-gas shift catalysts. Gold catalysts have proven to be very efficient for water-gas shift reaction at low temperature. The aim of the present study was to investigate the effect of:(i) different preparation methods(impregnation and coprecipitation) to obtain a modified ceria support,and(ii) the amount of Y_2 O_3(1.0 wt%, 2.5 wt%, 5.0 wt% and 7.5 wt%) as dopant on the water-gas shift activity of Au/CeO_2 catalysts. An extended characterization by means of S_(BET), XRD, HRTEM/HAADF, FTIR,H_2-TPR and CO-TPR measurements in combination with careful evaluation of the catalyst behavior allowed to shed light on the parameters governing the water-gas shift activity. The catalysts show very high activity(>90% CO conversion) in the temperature range 180-220 ℃,with a slightly better performance of the gold catalysts on supports prepared by impregnation. The decreased activity with increasing Y_2 O_3 concentration is related to the hindering of oxygen mobility due to ordering of surface oxygen vacancies in vicinity of segregated Y^(3+). The effect of catalyst pre-treatments and the stability of the best performing samples were examined as well.展开更多
The recombinant DNA technology enabled the produ-ction of a variety of human therapeutic proteins.Accumulated clinical experience,however,indicates that the formation of antibodies against such proteins is a general p...The recombinant DNA technology enabled the produ-ction of a variety of human therapeutic proteins.Accumulated clinical experience,however,indicates that the formation of antibodies against such proteins is a general phenomenon rather than an exception.The immunogenicity of therapeutic proteins results in inefficient therapy and in the development of undesired,sometimes life-threatening,side reactions.The human proteins,designed for clinical application,usually have the same amino acid sequence as their native prototypes and it is not yet fully clear what the reasons for their immunogenicity are.In previous studies we have demonstrated for the first time that interferon-b(IFN-b)pharmaceuticals,used for treatment of patients with multiple sclerosis,do contain advanced glycation end products(AGEs)that contribute to IFN-b immunogenicity.AGEs are the fnal products of a chemical reaction known as the Maillard reaction or glycation,which implication in protein drugs’immunogenicity has been overlooked so far.Therefore,the aim of the present article is to provide a comprehensive overview on the Maillard reaction with emphasis on experimental data and theoretical consideration telling us why the Maillard reaction warrants special attention in the context of the well-documented protein drugs’immunogenicity.展开更多
All mobile carriers these days have provided 3G and 4G services to their customers. The evolution of cellular networks from 3G to 4G has improved several performance metrics of the data communications. The focus of th...All mobile carriers these days have provided 3G and 4G services to their customers. The evolution of cellular networks from 3G to 4G has improved several performance metrics of the data communications. The focus of this paper is to evaluate two of the most important performance metrics: throughput and delay. We consider the cellular network as an integrate infrastructure that includes mobile and fixed nodes. Based on this model we calculate and analyze the throughput and delay. Our results illustrate that the throughput is increased while the delay is decreased in 4G data network compared to the previous 3G architecture. In addition, we evaluate how the delay affects the security of the network.展开更多
文摘This study demonstrates the complexity and importance of water quality as a measure of the health and sustainability of ecosystems that directly influence biodiversity,human health,and the world economy.The predictability of water quality thus plays a crucial role in managing our ecosystems to make informed decisions and,hence,proper environmental management.This study addresses these challenges by proposing an effective machine learning methodology applied to the“Water Quality”public dataset.The methodology has modeled the dataset suitable for providing prediction classification analysis with high values of the evaluating parameters such as accuracy,sensitivity,and specificity.The proposed methodology is based on two novel approaches:(a)the SMOTE method to deal with unbalanced data and(b)the skillfully involved classical machine learning models.This paper uses Random Forests,Decision Trees,XGBoost,and Support Vector Machines because they can handle large datasets,train models for handling skewed datasets,and provide high accuracy in water quality classification.A key contribution of this work is the use of custom sampling strategies within the SMOTE approach,which significantly enhanced performance metrics and improved class imbalance handling.The results demonstrate significant improvements in predictive performance,achieving the highest reported metrics:accuracy(98.92%vs.96.06%),sensitivity(98.3%vs.71.26%),and F1 score(98.37%vs.79.74%)using the XGBoost model.These improvements underscore the effectiveness of our custom SMOTE sampling strategies in addressing class imbalance.The findings contribute to environmental management by enabling ecology specialists to develop more accurate strategies for monitoring,assessing,and managing drinking water quality,ensuring better ecosystem and public health outcomes.
基金supported by the Bulgarian National Science Fund(ContractдH09/5/2016)the CONACYT PDCPN 1216 and the University of Turin(Ricerca Locale 2016-2017)
文摘The utilization of pure hydrogen as an energy source in fuel cells gave rise to renewed interest in developing active and stable water-gas shift catalysts. Gold catalysts have proven to be very efficient for water-gas shift reaction at low temperature. The aim of the present study was to investigate the effect of:(i) different preparation methods(impregnation and coprecipitation) to obtain a modified ceria support,and(ii) the amount of Y_2 O_3(1.0 wt%, 2.5 wt%, 5.0 wt% and 7.5 wt%) as dopant on the water-gas shift activity of Au/CeO_2 catalysts. An extended characterization by means of S_(BET), XRD, HRTEM/HAADF, FTIR,H_2-TPR and CO-TPR measurements in combination with careful evaluation of the catalyst behavior allowed to shed light on the parameters governing the water-gas shift activity. The catalysts show very high activity(>90% CO conversion) in the temperature range 180-220 ℃,with a slightly better performance of the gold catalysts on supports prepared by impregnation. The decreased activity with increasing Y_2 O_3 concentration is related to the hindering of oxygen mobility due to ordering of surface oxygen vacancies in vicinity of segregated Y^(3+). The effect of catalyst pre-treatments and the stability of the best performing samples were examined as well.
文摘The recombinant DNA technology enabled the produ-ction of a variety of human therapeutic proteins.Accumulated clinical experience,however,indicates that the formation of antibodies against such proteins is a general phenomenon rather than an exception.The immunogenicity of therapeutic proteins results in inefficient therapy and in the development of undesired,sometimes life-threatening,side reactions.The human proteins,designed for clinical application,usually have the same amino acid sequence as their native prototypes and it is not yet fully clear what the reasons for their immunogenicity are.In previous studies we have demonstrated for the first time that interferon-b(IFN-b)pharmaceuticals,used for treatment of patients with multiple sclerosis,do contain advanced glycation end products(AGEs)that contribute to IFN-b immunogenicity.AGEs are the fnal products of a chemical reaction known as the Maillard reaction or glycation,which implication in protein drugs’immunogenicity has been overlooked so far.Therefore,the aim of the present article is to provide a comprehensive overview on the Maillard reaction with emphasis on experimental data and theoretical consideration telling us why the Maillard reaction warrants special attention in the context of the well-documented protein drugs’immunogenicity.
文摘All mobile carriers these days have provided 3G and 4G services to their customers. The evolution of cellular networks from 3G to 4G has improved several performance metrics of the data communications. The focus of this paper is to evaluate two of the most important performance metrics: throughput and delay. We consider the cellular network as an integrate infrastructure that includes mobile and fixed nodes. Based on this model we calculate and analyze the throughput and delay. Our results illustrate that the throughput is increased while the delay is decreased in 4G data network compared to the previous 3G architecture. In addition, we evaluate how the delay affects the security of the network.
