In order to improve the end-point hit rate of basic oxygen furnace steelmaking,a novel dynamic control model was proposed based on an improved twin support vector regression algorithm.The controlled objects were the e...In order to improve the end-point hit rate of basic oxygen furnace steelmaking,a novel dynamic control model was proposed based on an improved twin support vector regression algorithm.The controlled objects were the end-point carbon content and temperature.The proposed control model was established by using the low carbon steel samples collected from a steel plant,which consists of two prediction models,a preprocess model,two regulation units,a controller and a basic oxygen furnace.The test results of 100 heats show that the prediction models can achieve a double hit rate of 90%within the error bound of 0.005 wt.%C and 15℃.The preprocess model was used to predict an initial end-blow oxygen volume.However,the double hit rate of the carbon con tent and temperature only achieves 65%.Then,the oxygen volume and coolant additi ons were adjusted by the regulation units to improve the hit rate.Finally,the double hit rate after the regulation is reached up to 90%.The results indicate that the proposed dynamic control model is efficient to guide the real production for low carbon steel,and the modeling method is also suitable for the applications of other steel grades.展开更多
Here we firstly report a series of new deep eutectic solvents(DESs) induced by small amounts of crown ether complex and mainly formed by polyethylene glycol. These DESs not only presented the ultra-deep extraction of ...Here we firstly report a series of new deep eutectic solvents(DESs) induced by small amounts of crown ether complex and mainly formed by polyethylene glycol. These DESs not only presented the ultra-deep extraction of non-basic N-compounds from fuel oils, but also opened up the possibility of other new applications in chemistry and materials science.展开更多
RGD-containing peptide （ K16-GRGDSPC） , characterized as non-viral gene vectors, was fabricated to modify the surface of PLGA-[ASP- PEG] matrix, which offered the foundation for gene transfer with porous matrix of g...RGD-containing peptide （ K16-GRGDSPC） , characterized as non-viral gene vectors, was fabricated to modify the surface of PLGA-[ASP- PEG] matrix, which offered the foundation for gene transfer with porous matrix of gene activated later. Peptide was synthesized and matrix was executed into chips A, B and chip C. Chip C was regarded as control. Chips A and B were reacted with cross-linker. Then chip A was reacted with peptide. MS and HPLC were ased to detect the .14W and purity of peptide. Sulphur, existing on the surface of biomaterials, was detected by XPS. The purity of un-reacted peptide in residual solution was detected by a spectrophotometer. HPLC shows that the peptide purity was 94%- 95% , and MS shows that the MW was 2 741. 3307. XPS reveals that the binding energy of sulphur was 164 eV and the ratio of carbon to sulphur （C/S） was 99. 746 ：0. 1014 in reacted chip A. The binding energy of sulphur in reacted chip B was 164 eV and 162 eV, C/ S was 99.574：0.4255, aM there was no sulphur in chip C. Peptide was manufactured and linked to the surface of biomimetic and 3-D matrix, which offered the possibilities for gene transfer and tissue engineering with this new kind of non-viral gene vector.展开更多
We evaluated the effects of rice black streak dwarf virus （RBSDV）-infested rice plants on the ecological parameters and its relevant defensive and detoxification enzymes of white-backed planthopper （WBPH） in labor...We evaluated the effects of rice black streak dwarf virus （RBSDV）-infested rice plants on the ecological parameters and its relevant defensive and detoxification enzymes of white-backed planthopper （WBPH） in laboratory for exploring the relationship between RBSDV and the non-vector planthopper. The results showed that nymph survival rate, female adult weight and fecundity, and egg hatchability of WBPH fed on RBSDV-infested rice plants did not markedly differ from those on healthy plants, whereas the female adult longevity and egg duration significantly shortened on diseased plants. Furthermore, significantly higher activities of defensive enzymes （dismutase, catalase and peroxidase） and detoxification enzymes （acetylcholinesterase, carboxylesterase and glutathione S-transferase） were found in WBPH adults fed on infected plants. Results implied that infestation by RBSDV increased the ecological fitness of non-vector planthopper population.展开更多
In this paper, sixty-eight research articles published between 2000 and 2017 as well as textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN), Support Vector Machines (SVM), Random Forest (...In this paper, sixty-eight research articles published between 2000 and 2017 as well as textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN), Support Vector Machines (SVM), Random Forest (RF) and Neural Network (NN) as the main statistical tools were reviewed. The aim was to examine and compare these nonparametric classification methods on the following attributes: robustness to training data, sensitivity to changes, data fitting, stability, ability to handle large data sizes, sensitivity to noise, time invested in parameter tuning, and accuracy. The performances, strengths and shortcomings of each of the algorithms were examined, and finally, a conclusion was arrived at on which one has higher performance. It was evident from the literature reviewed that RF is too sensitive to small changes in the training dataset and is occasionally unstable and tends to overfit in the model. KNN is easy to implement and understand but has a major drawback of becoming significantly slow as the size of the data in use grows, while the ideal value of K for the KNN classifier is difficult to set. SVM and RF are insensitive to noise or overtraining, which shows their ability in dealing with unbalanced data. Larger input datasets will lengthen classification times for NN and KNN more than for SVM and RF. Among these nonparametric classification methods, NN has the potential to become a more widely used classification algorithm, but because of their time-consuming parameter tuning procedure, high level of complexity in computational processing, the numerous types of NN architectures to choose from and the high number of algorithms used for training, most researchers recommend SVM and RF as easier and wieldy used methods which repeatedly achieve results with high accuracies and are often faster to implement.展开更多
We solve the Duffin-Kemmer-Petiau （DKP） equation with a non-minimal vector Yukawa potential in （1＋1）- dimensional spa^e-time for spin-1 particles. The Nikiforov Uvarov method is used in the calculations, and the ...We solve the Duffin-Kemmer-Petiau （DKP） equation with a non-minimal vector Yukawa potential in （1＋1）- dimensional spa^e-time for spin-1 particles. The Nikiforov Uvarov method is used in the calculations, and the eigen- functions as well as the energy eigenvalues are obtained in a proper Pekeris-type approximation.展开更多
In the article, we established a non-autonomous vector infectious disease model, studied the long-term dynamic behavior of the system, and obtained sufficient conditions for the extinction and persistence of infectiou...In the article, we established a non-autonomous vector infectious disease model, studied the long-term dynamic behavior of the system, and obtained sufficient conditions for the extinction and persistence of infectious diseases by constructing integral functions.展开更多
Objective: To explore the expression of vascular endothelial growth factor(VEGF) and basic fibroblast growth factor(bFGF) in non-small cell lung cancer(NSCLC) and theIR clinical significance. Methods: The expression o...Objective: To explore the expression of vascular endothelial growth factor(VEGF) and basic fibroblast growth factor(bFGF) in non-small cell lung cancer(NSCLC) and theIR clinical significance. Methods: The expression of VEGF and bFGF was examined at the protein levels by immunohistochemical staining in 96 NSCLC patients, and in 36 of which at the mRNA levels by reverse transcription-PCR analysis. Results: VEGF mRNAs were expressed predominately as its secretory forms (VEGF121 and VEGF165) in NSCLC tissues. The positive ratios of VEGF121 and VEGF165 were 69.5%(25 of 36) and 41.7%(15 of 36) respectively. The positive ratio of bFGF was 52.8(19 of 36) in the same tumor specimens. The positive ratios of VEGF and bFGF at protein levels were 55.55%(20 of 36) and 58.33%(21 of 36) respectively. A significant positive correlation was observed between VEGF and bFGF expression in NSCLC tissues(P=0.002). No significant interrelationship between VEGF, bFGF expression and clinical data(age, sex, histological subtype differentiation, P-stage, metastasis and survival) was found. Conclusions: VEGF and bFGF may play an important role in angiogenesis and act in a synergistic manner in NSCLC.展开更多
A great number of semi-analytical models, notably the representation of electromagnetic fields by integral equations are based on the second order vector potential (SOVP) formalism which introduces two scalar potentia...A great number of semi-analytical models, notably the representation of electromagnetic fields by integral equations are based on the second order vector potential (SOVP) formalism which introduces two scalar potentials in order to obtain analytical expressions of the electromagnetic fields from the two potentials. However, the scalar decomposition is often known for canonical coordinate systems. This paper aims in introducing a specific SOVP formulation dedicated to arbitrary non-orthogonal curvilinear coordinates systems. The electromagnetic field representation which is derived in this paper constitutes the key stone for the development of semi-analytical models for solving some eddy currents moelling problems and electromagnetic radiation problems considering at least two homogeneous media separated by a rough interface. This SOVP formulation is derived from the tensor formalism and Maxwell’s equations written in a non-orthogonal coordinates system adapted to a surface characterized by a 2D arbitrary aperiodic profile.展开更多
This paper presents a modeling method for a non-uniformly sampled system bused on support vector regression （ SVR ）. First, a lifted discrete-time state-space model for a non-uniformly sampled system is derived by u...This paper presents a modeling method for a non-uniformly sampled system bused on support vector regression （ SVR ）. First, a lifted discrete-time state-space model for a non-uniformly sampled system is derived by using the lifting technique to reduce the modeling difficulty caused by multirate sampling. Then, the system is divided into several parallel subsystems and their input-output model is presented to satisfy the SVR model. Finally, an on-line SVR technique is utilized to establish the models of all subsystems to deal with uncertainty. Furthermore, the presented method is applied in a multichannel electrohydraulic force servo synchronous loading system to predict the system outputs over the control sample interval and the prediction mean absolute percentage error reaches 0. 092%. The results demonstrate that the presented method has a high modeling precision and the subsystems have the same level of prediction error.展开更多
BACKGROUND:There are several reasons why resuscitation measures may lead to inferior results:difficulties in team building,delayed realization of the emergency and interruption of chest compression.This study investig...BACKGROUND:There are several reasons why resuscitation measures may lead to inferior results:difficulties in team building,delayed realization of the emergency and interruption of chest compression.This study investigated the outcome of a new form of in-hospital cardiopulmonary resuscitation(CPR) training with special focus on changes in self-assurance of potential helpers when faced with emergency situations.METHODS:Following a 12-month period of CPR training,questionnaires were distributed to participants and non-participants.Those non-participants who intended to undergo the training at a later date served as control group.RESULTS:The study showed that participants experienced a significant improvement in selfassurance,compared with their remembered self-assurance before the training.Their self-assurance also was significantly greater than that of the control group of non-participants.CONCLUSION:Short lessons in CPR have an impact on the self-assurance of medical and non-medical personnel.展开更多
Upon the discovery of RNA interference(RNAi),canonical small interfering RNA(si RNA) has been recognized to trigger sequence-specific gene silencing. Despite the benefits of si RNAs as potential new drugs,there are ob...Upon the discovery of RNA interference(RNAi),canonical small interfering RNA(si RNA) has been recognized to trigger sequence-specific gene silencing. Despite the benefits of si RNAs as potential new drugs,there are obstacles still to be overcome,including off-target effects and immune stimulation. More recently,Dicer substrate si RNA(Dsi RNA) has been introduced as an alternative to si RNA. Similarly,it also is proving to be potent and target-specific,while rendering less immune stimulation. Dsi RNA is 25–30 nucleotides in length,and is further cleaved and processed by the Dicer enzyme. As with si RNA,it is crucial to design and develop a stable,safe,and efficient system for the delivery of Dsi RNA into the cytoplasm of targeted cells. Several polymeric nanoparticle systems have been well established to load Dsi RNA for in vitro and in vivo delivery,thereby overcoming a major hurdle in the therapeutic uses of Dsi RNA. The present review focuses on a comparison of si RNA and Dsi RNA on the basis of their design,mechanism,in vitro and in vivo delivery,and therapeutics.展开更多
The identification of activity locations in con- tinuous GPS trajectories is an essential preliminary step in obtaining person trip data and for activity-based trans- portation demand forecasting. In this research, a ...The identification of activity locations in con- tinuous GPS trajectories is an essential preliminary step in obtaining person trip data and for activity-based trans- portation demand forecasting. In this research, a two-step methodology for identifying activity stop locations is pro- posed. In the first step, an improved density-based spatial clustering of applications with noise （DBSCAN） algorithm identifies stop points and moving points; then in the second step, the support vector machines （SVMs） method distin- guishes activity stops from non-activity stops among the identified stop points. A time sequence constraint and a direction change constraint are applied as improvements to DBSCAN （yielding an improved algorithm known as C-DBSCAN）. Then three major features are extracted for use in the SVMs method： stop duration, mean distance to the centroid of a cluster of points at a stop location, and the shorter of distances from current location to home and to the workplace. The proposed methodology was tested using GPS data collected from mobile phones in the Nagoya area of Japan. The C-DBSCAN algorithm achieves an accuracy of 90 % in identifying stop points in the first step, while the SVMs method is 96 % accurate in distin- guishing the locations of activity stops from non-activity stops in the second step. Compared to other variants of DBSCAN used to identify activity locations from GPS trajectories, this two-step method is generally superior.展开更多
基金This work was supported by Liaoning Province PhD Start-up Fund(No.201601291)Liaoning Province Ministry of Education Scientific Study Project(No.2O17LNQN11).
文摘In order to improve the end-point hit rate of basic oxygen furnace steelmaking,a novel dynamic control model was proposed based on an improved twin support vector regression algorithm.The controlled objects were the end-point carbon content and temperature.The proposed control model was established by using the low carbon steel samples collected from a steel plant,which consists of two prediction models,a preprocess model,two regulation units,a controller and a basic oxygen furnace.The test results of 100 heats show that the prediction models can achieve a double hit rate of 90%within the error bound of 0.005 wt.%C and 15℃.The preprocess model was used to predict an initial end-blow oxygen volume.However,the double hit rate of the carbon con tent and temperature only achieves 65%.Then,the oxygen volume and coolant additi ons were adjusted by the regulation units to improve the hit rate.Finally,the double hit rate after the regulation is reached up to 90%.The results indicate that the proposed dynamic control model is efficient to guide the real production for low carbon steel,and the modeling method is also suitable for the applications of other steel grades.
基金supported by the National Natrual Sciece Foundation of China (Nos. 21650110454, 21675164, 2 822407)the CAS-President International Fellowship Initiative (No. 2017PC0014)the Funds for Distinguished Young Scientists of Gansu (No. 1506RJDA281)
文摘Here we firstly report a series of new deep eutectic solvents(DESs) induced by small amounts of crown ether complex and mainly formed by polyethylene glycol. These DESs not only presented the ultra-deep extraction of non-basic N-compounds from fuel oils, but also opened up the possibility of other new applications in chemistry and materials science.
文摘RGD-containing peptide （ K16-GRGDSPC） , characterized as non-viral gene vectors, was fabricated to modify the surface of PLGA-[ASP- PEG] matrix, which offered the foundation for gene transfer with porous matrix of gene activated later. Peptide was synthesized and matrix was executed into chips A, B and chip C. Chip C was regarded as control. Chips A and B were reacted with cross-linker. Then chip A was reacted with peptide. MS and HPLC were ased to detect the .14W and purity of peptide. Sulphur, existing on the surface of biomaterials, was detected by XPS. The purity of un-reacted peptide in residual solution was detected by a spectrophotometer. HPLC shows that the peptide purity was 94%- 95% , and MS shows that the MW was 2 741. 3307. XPS reveals that the binding energy of sulphur was 164 eV and the ratio of carbon to sulphur （C/S） was 99. 746 ：0. 1014 in reacted chip A. The binding energy of sulphur in reacted chip B was 164 eV and 162 eV, C/ S was 99.574：0.4255, aM there was no sulphur in chip C. Peptide was manufactured and linked to the surface of biomimetic and 3-D matrix, which offered the possibilities for gene transfer and tissue engineering with this new kind of non-viral gene vector.
基金supported by the National Basic Research Program of China(Grant No.2010CB126200)the AgroIndustry R&D Special Fund of China(Grant Nos.200903051 and 201003031)
文摘We evaluated the effects of rice black streak dwarf virus （RBSDV）-infested rice plants on the ecological parameters and its relevant defensive and detoxification enzymes of white-backed planthopper （WBPH） in laboratory for exploring the relationship between RBSDV and the non-vector planthopper. The results showed that nymph survival rate, female adult weight and fecundity, and egg hatchability of WBPH fed on RBSDV-infested rice plants did not markedly differ from those on healthy plants, whereas the female adult longevity and egg duration significantly shortened on diseased plants. Furthermore, significantly higher activities of defensive enzymes （dismutase, catalase and peroxidase） and detoxification enzymes （acetylcholinesterase, carboxylesterase and glutathione S-transferase） were found in WBPH adults fed on infected plants. Results implied that infestation by RBSDV increased the ecological fitness of non-vector planthopper population.
文摘In this paper, sixty-eight research articles published between 2000 and 2017 as well as textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN), Support Vector Machines (SVM), Random Forest (RF) and Neural Network (NN) as the main statistical tools were reviewed. The aim was to examine and compare these nonparametric classification methods on the following attributes: robustness to training data, sensitivity to changes, data fitting, stability, ability to handle large data sizes, sensitivity to noise, time invested in parameter tuning, and accuracy. The performances, strengths and shortcomings of each of the algorithms were examined, and finally, a conclusion was arrived at on which one has higher performance. It was evident from the literature reviewed that RF is too sensitive to small changes in the training dataset and is occasionally unstable and tends to overfit in the model. KNN is easy to implement and understand but has a major drawback of becoming significantly slow as the size of the data in use grows, while the ideal value of K for the KNN classifier is difficult to set. SVM and RF are insensitive to noise or overtraining, which shows their ability in dealing with unbalanced data. Larger input datasets will lengthen classification times for NN and KNN more than for SVM and RF. Among these nonparametric classification methods, NN has the potential to become a more widely used classification algorithm, but because of their time-consuming parameter tuning procedure, high level of complexity in computational processing, the numerous types of NN architectures to choose from and the high number of algorithms used for training, most researchers recommend SVM and RF as easier and wieldy used methods which repeatedly achieve results with high accuracies and are often faster to implement.
文摘We solve the Duffin-Kemmer-Petiau （DKP） equation with a non-minimal vector Yukawa potential in （1＋1）- dimensional spa^e-time for spin-1 particles. The Nikiforov Uvarov method is used in the calculations, and the eigen- functions as well as the energy eigenvalues are obtained in a proper Pekeris-type approximation.
文摘In the article, we established a non-autonomous vector infectious disease model, studied the long-term dynamic behavior of the system, and obtained sufficient conditions for the extinction and persistence of infectious diseases by constructing integral functions.
基金This work was supported by a grant from the Beijing Natural Science Foundation (No.7992005) and from plan of new star of science and technology of Beijing(No. 99-148).
文摘Objective: To explore the expression of vascular endothelial growth factor(VEGF) and basic fibroblast growth factor(bFGF) in non-small cell lung cancer(NSCLC) and theIR clinical significance. Methods: The expression of VEGF and bFGF was examined at the protein levels by immunohistochemical staining in 96 NSCLC patients, and in 36 of which at the mRNA levels by reverse transcription-PCR analysis. Results: VEGF mRNAs were expressed predominately as its secretory forms (VEGF121 and VEGF165) in NSCLC tissues. The positive ratios of VEGF121 and VEGF165 were 69.5%(25 of 36) and 41.7%(15 of 36) respectively. The positive ratio of bFGF was 52.8(19 of 36) in the same tumor specimens. The positive ratios of VEGF and bFGF at protein levels were 55.55%(20 of 36) and 58.33%(21 of 36) respectively. A significant positive correlation was observed between VEGF and bFGF expression in NSCLC tissues(P=0.002). No significant interrelationship between VEGF, bFGF expression and clinical data(age, sex, histological subtype differentiation, P-stage, metastasis and survival) was found. Conclusions: VEGF and bFGF may play an important role in angiogenesis and act in a synergistic manner in NSCLC.
文摘A great number of semi-analytical models, notably the representation of electromagnetic fields by integral equations are based on the second order vector potential (SOVP) formalism which introduces two scalar potentials in order to obtain analytical expressions of the electromagnetic fields from the two potentials. However, the scalar decomposition is often known for canonical coordinate systems. This paper aims in introducing a specific SOVP formulation dedicated to arbitrary non-orthogonal curvilinear coordinates systems. The electromagnetic field representation which is derived in this paper constitutes the key stone for the development of semi-analytical models for solving some eddy currents moelling problems and electromagnetic radiation problems considering at least two homogeneous media separated by a rough interface. This SOVP formulation is derived from the tensor formalism and Maxwell’s equations written in a non-orthogonal coordinates system adapted to a surface characterized by a 2D arbitrary aperiodic profile.
文摘This paper presents a modeling method for a non-uniformly sampled system bused on support vector regression （ SVR ）. First, a lifted discrete-time state-space model for a non-uniformly sampled system is derived by using the lifting technique to reduce the modeling difficulty caused by multirate sampling. Then, the system is divided into several parallel subsystems and their input-output model is presented to satisfy the SVR model. Finally, an on-line SVR technique is utilized to establish the models of all subsystems to deal with uncertainty. Furthermore, the presented method is applied in a multichannel electrohydraulic force servo synchronous loading system to predict the system outputs over the control sample interval and the prediction mean absolute percentage error reaches 0. 092%. The results demonstrate that the presented method has a high modeling precision and the subsystems have the same level of prediction error.
文摘BACKGROUND:There are several reasons why resuscitation measures may lead to inferior results:difficulties in team building,delayed realization of the emergency and interruption of chest compression.This study investigated the outcome of a new form of in-hospital cardiopulmonary resuscitation(CPR) training with special focus on changes in self-assurance of potential helpers when faced with emergency situations.METHODS:Following a 12-month period of CPR training,questionnaires were distributed to participants and non-participants.Those non-participants who intended to undergo the training at a later date served as control group.RESULTS:The study showed that participants experienced a significant improvement in selfassurance,compared with their remembered self-assurance before the training.Their self-assurance also was significantly greater than that of the control group of non-participants.CONCLUSION:Short lessons in CPR have an impact on the self-assurance of medical and non-medical personnel.
基金financial support received from Centre of Research and Instrumentation (CRIM), Universiti Kebangsaan Malaysia
文摘Upon the discovery of RNA interference(RNAi),canonical small interfering RNA(si RNA) has been recognized to trigger sequence-specific gene silencing. Despite the benefits of si RNAs as potential new drugs,there are obstacles still to be overcome,including off-target effects and immune stimulation. More recently,Dicer substrate si RNA(Dsi RNA) has been introduced as an alternative to si RNA. Similarly,it also is proving to be potent and target-specific,while rendering less immune stimulation. Dsi RNA is 25–30 nucleotides in length,and is further cleaved and processed by the Dicer enzyme. As with si RNA,it is crucial to design and develop a stable,safe,and efficient system for the delivery of Dsi RNA into the cytoplasm of targeted cells. Several polymeric nanoparticle systems have been well established to load Dsi RNA for in vitro and in vivo delivery,thereby overcoming a major hurdle in the therapeutic uses of Dsi RNA. The present review focuses on a comparison of si RNA and Dsi RNA on the basis of their design,mechanism,in vitro and in vivo delivery,and therapeutics.
基金supported by Grant-in-Aid for Scientific Research(No.25630215 and 26220906)from the Ministry of Education,Culture,Sports,Science,and Technology,Japanthe Japan Society for the Promotion of Science
文摘The identification of activity locations in con- tinuous GPS trajectories is an essential preliminary step in obtaining person trip data and for activity-based trans- portation demand forecasting. In this research, a two-step methodology for identifying activity stop locations is pro- posed. In the first step, an improved density-based spatial clustering of applications with noise （DBSCAN） algorithm identifies stop points and moving points; then in the second step, the support vector machines （SVMs） method distin- guishes activity stops from non-activity stops among the identified stop points. A time sequence constraint and a direction change constraint are applied as improvements to DBSCAN （yielding an improved algorithm known as C-DBSCAN）. Then three major features are extracted for use in the SVMs method： stop duration, mean distance to the centroid of a cluster of points at a stop location, and the shorter of distances from current location to home and to the workplace. The proposed methodology was tested using GPS data collected from mobile phones in the Nagoya area of Japan. The C-DBSCAN algorithm achieves an accuracy of 90 % in identifying stop points in the first step, while the SVMs method is 96 % accurate in distin- guishing the locations of activity stops from non-activity stops in the second step. Compared to other variants of DBSCAN used to identify activity locations from GPS trajectories, this two-step method is generally superior.
