BACKGROUND Gastro-esophageal reflux disease(GERD)may affect the upper digestive tract;up to 20%of population in Western nations are affected by GERD.Antacids,histamine H2-receptor antagonists,and Proton Pump Inhibitor...BACKGROUND Gastro-esophageal reflux disease(GERD)may affect the upper digestive tract;up to 20%of population in Western nations are affected by GERD.Antacids,histamine H2-receptor antagonists,and Proton Pump Inhibitors(PPIs)are considered the referring medications for GERD.Nevertheless,PPIs must be managed carefully because their use,especially chronic,could be linked with some adverse effects.An effective and safe alternative pharmacological tool for GERD is needed.After the identification of potentially new medications to flank PPIs,it is mandatory to revise and improve good clinical practices even through a consensus process.AIM To optimize diagnosis and treatment guidelines for GERD through a consensus based on Delphi method.METHODS The availability of clinical studies describing the action of the multicomponent/multitarget medication Nux vomica-Heel,subject of the consensus,is the basic prerequisite for the consensus itself.A modified Delphi process was used to reach a consensus among a panel of Italian GERD specialists on the overlapping approach PPIs/Nux vomica-Heel as a new intervention model for the management of GERD.The Voting Consensus group was composed of 49 Italian Medical Doctors with different specializations:Gastroenterology,otolaryngology,geriatrics,and general medicine.A scientific committee analyzed the literature,determined areas that required investigation(in agreement with the multiple-choice questionnaire results),and identified two topics of interest:(1)GERD disease;and(2)GERD treatment.Statements for each of these topics were then formulated and validated.The Delphi process involved two rounds of questioning submitted to the panel experts using an online platform.RESULTS According to their routinary GERD practice and current clinical evidence,the panel members provided feedback to each questionnaire statement.The experts evaluated 15 statements and reached consensus on all 15.The statements regarding the GERD disease showed high levels of agreement,with consensus ranging from 70%to 92%.The statements regarding the GERD treatment also showed very high levels of agreement,with consensus ranging from 90%to 100%.This Delphi process was able to reach consensus among physicians in relevant aspects of GERD management,such as the adoption of a new approach to treat patients with GERD based on the overlapping between PPIs and Nux vomica-Heel.The consensus was unanimous among the physicians with different specializations,underlying the uniqueness of the agreement reached to identify in the overlapping approach between PPIs and Nux vomica-Heel a new intervention model for GERD management.The results support that an effective approach to deprescribe PPIs through a progressive decalage timetable(reducing PPIs administration to as-needed use),should be considered.CONCLUSION Nux vomica-Heel appears to be a valid opportunity for GERD treatment to favor the deprescription of PPIs and to maintain low disease activity together with the symptomatology remission.展开更多
The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the intera...The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.展开更多
BACKGROUND Infections by non-tuberculous mycobacteria(NTM)have become more common in recent years.Mycobacterium canariasense(M.canariasense)was first reported as an opportunistic pathogen in 2004,but there have been v...BACKGROUND Infections by non-tuberculous mycobacteria(NTM)have become more common in recent years.Mycobacterium canariasense(M.canariasense)was first reported as an opportunistic pathogen in 2004,but there have been very few case reports since then.Nocardia is a genus of aerobic and Gram-positive bacilli,and these species are also opportunistic pathogens and in the Mycobacteriales order.Conventional methods for diagnosis of NTM are inefficient.Metagenomic next-generation sequencing(mNGS)can rapidly detect many pathogenic microorganisms,even rare species.Most NTM and Nocardia infections occur in immunocompromised patients with atypical clinical symptoms.There are no previous reports of infection by M.canariasense and Nocardia farcinica(N.farcinica),especially in immunocompetent patients.This case report describes an immunocompetent 52-year-old woman who had overlapping infections of M.canariasense,N.farcinica,and Candida parapsilosis(C.parapsilosis)based on mNGS.CASE SUMMARY A 52-year-old woman presented with a productive cough and chest pain for 2 wk,and recurrent episodes of moderate-grade fever for 1 wk.She received antibiotics for 1 wk at a local hospital,and experienced defervescence,but the productive cough and chest pain persisted.We collected samples of a lung lesion and alveolar lavage fluid for mNGS.The lung tissue was positive for M.canariasense,N.farcinica,and C.parapsilosis,and the alveolar lavage fluid was positive for M.canariasense.The diagnosis was pneumonia,and application of appropriate antibiotic therapy cured the patient.CONCLUSION Etiological diagnosis is critical for patients with infectious diseases.mNGS can identify rare and novel pathogens,and does not require a priori knowledge.展开更多
Since the new curriculum reform,labor education has gradually shed its marginalized position in the“five educations,”and the labor curriculum has become an independent course officially separated from comprehensive ...Since the new curriculum reform,labor education has gradually shed its marginalized position in the“five educations,”and the labor curriculum has become an independent course officially separated from comprehensive practical activity courses.Exploring the practical path of labor curriculum in compulsory education in China has become the primary task of labor education in China.Based on the practical situation of labor curriculum in compulsory education in China,drawing on the theory of overlapping influence domains,and from the perspective of collaborative education among family,school,and community,this paper proposes a curriculum practical path of“school-led”family-school-community collaboration and a curriculum practical path guided by“student-centered”sentiment,in order to provide references for the practice of labor curriculum in compulsory education in China.展开更多
There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computin...There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computing and clustering is introduced to solve the above problems so as to accurately describe the similarity between nodes and fully explore the multi-community structure.A Set Pair Three-Way Overlapping Community Discovery Algorithm for Weighted Social Internet of Things(WSIoT-SPTOCD)is proposed.In the local network structure,which fully considers the topological information between nodes,the set pair connection degree is used to analyze the identity,difference and reverse of neighbor nodes.The similarity degree of different neighbor nodes is defined from network edge weight and node degree,and the similarity measurement method of set pair between nodes based on the local information structure is proposed.According to the number of nodes'neighbors and the connection degree of adjacent edges,the clustering intensity of nodes is defined,and an improved algorithm for initial value selection of k-means is proposed.The nodes are allocated according to the set pair similarity between nodes and different communities.Three-way community structures composed of a positive domain,boundary domain and negative domain are generated iteratively.Next,the overlapping node set is generated according to the calculation results of community node membership.Finally,experiments are carried out on artificial networks and real networks.The results show that WSIoT-SPTOCD performs well in terms of standardized mutual information,overlapping community modularity and F1.展开更多
Most modern technologies,such as social media,smart cities,and the internet of things(IoT),rely on big data.When big data is used in the real-world applications,two data challenges such as class overlap and class imba...Most modern technologies,such as social media,smart cities,and the internet of things(IoT),rely on big data.When big data is used in the real-world applications,two data challenges such as class overlap and class imbalance arises.When dealing with large datasets,most traditional classifiers are stuck in the local optimum problem.As a result,it’s necessary to look into new methods for dealing with large data collections.Several solutions have been proposed for overcoming this issue.The rapid growth of the available data threatens to limit the usefulness of many traditional methods.Methods such as oversampling and undersampling have shown great promises in addressing the issues of class imbalance.Among all of these techniques,Synthetic Minority Oversampling TechniquE(SMOTE)has produced the best results by generating synthetic samples for the minority class in creating a balanced dataset.The issue is that their practical applicability is restricted to problems involving tens of thousands or lower instances of each.In this paper,we have proposed a parallel mode method using SMOTE and MapReduce strategy,this distributes the operation of the algorithm among a group of computational nodes for addressing the aforementioned problem.Our proposed solution has been divided into three stages.Thefirst stage involves the process of splitting the data into different blocks using a mapping function,followed by a pre-processing step for each mapping block that employs a hybrid SMOTE algo-rithm for solving the class imbalanced problem.On each map block,a decision tree model would be constructed.Finally,the decision tree blocks would be com-bined for creating a classification model.We have used numerous datasets with up to 4 million instances in our experiments for testing the proposed scheme’s cap-abilities.As a result,the Hybrid SMOTE appears to have good scalability within the framework proposed,and it also cuts down the processing time.展开更多
This work is concerned with the analysis of blood flow through inclined catheterized arteries having a balloon(angioplasty) with time-variant overlapping stenosis. The nature of blood in small arteries is analyzed mat...This work is concerned with the analysis of blood flow through inclined catheterized arteries having a balloon(angioplasty) with time-variant overlapping stenosis. The nature of blood in small arteries is analyzed mathematically by considering it as a Carreau nanofluid. The highly nonlinear momentum equations of nanofluid model are simplified by considering the mild stenosis case. The formulated problem is solved by a homotopy perturbation expansion in terms of a variant of the Weissenberg number to obtain explicit forms for the axial velocity, the stream function, the pressure gradient, the resistance impedance and the wall shear stress distribution. These solutions depend on the Brownian motion number, thermophoresis number, local temperature Grashof number G_r and local nanoparticle Grash of number B_r. The results were also studied for various values of the physical parameters, such as the Weissenberg number W_i, the power law index n, the taper angle φ, the maximum height of stenosis δ~*, the angle of inclination α, the maximum height of balloon σ~*, the axial displacement of the balloon z_d~*,the flow rate F and the Froud number Fr. The obtained results show that the transmission of axial velocity curves through a Newtonian fluid(Wi=0, n=1, Gr=0, Br=0, Nt=0, Nb≠0) is substantially lower than that through a Carreau nanofluid near the wall of balloon while the inverse occurs in the region between the balloon and stenosis. The streamlines have a clearly distinguished shifting toward the stenotic region and this shifting appears near the wall of the balloon, while it has almost disappeared near the stenotic wall and the trapping bolus in the case of horizontal arteries and Newtonian fluid(Wi=0, n=1, Gr=0, Br=0, Nt=0, Nb≠0) does not appear but for the case of Carreau nanofluid bolus appears.展开更多
The finite element method is presented to attain the numerical simulation of the residual stresses field in the material treated by laser shock processing. The distribution of residual stresses generated by a single l...The finite element method is presented to attain the numerical simulation of the residual stresses field in the material treated by laser shock processing. The distribution of residual stresses generated by a single laser shock with square and round laser spot is predicted and validated by experimental results. With the Finite Element Method (FEM) model, effects of different overlapping rates and impact sequences on the distribution of residual stresses are simulated. The results indicate that: (1) Overlapping laser shock can increase the compressive residual stresses. However, it is not effective on the growth of plastically affected depth; (2) Overlapping rate should be optimized and selected carefully for the large area treatment. Appropriate overlapping rate is beneficial to obtain a homogeneous residual stress field; (3) The impact sequence has a great effect on the residual stress field. It can greatly attenuate the phenomenon of the “residual stress hole” to obtain a homogeneous residual stress field.展开更多
Community detection is an important methodology for understanding the intrinsic structure and function of a realworld network. In this paper, we propose an effective and efficient algorithm, called Dominant Label Prop...Community detection is an important methodology for understanding the intrinsic structure and function of a realworld network. In this paper, we propose an effective and efficient algorithm, called Dominant Label Propagation Algorithm(Abbreviated as DLPA), to detect communities in complex networks. The algorithm simulates a special voting process to detect overlapping and non-overlapping community structure in complex networks simultaneously. Our algorithm is very efficient, since its computational complexity is almost linear to the number of edges in the network. Experimental results on both real-world and synthetic networks show that our algorithm also possesses high accuracies on detecting community structure in networks.展开更多
The effect of overlapping treatment on microstructure of laser clad WC/Ni60A composite coating was studied with XRD, SEM, TEM and SAED etc. The results show that during the overlapping treatment the existence of the ...The effect of overlapping treatment on microstructure of laser clad WC/Ni60A composite coating was studied with XRD, SEM, TEM and SAED etc. The results show that during the overlapping treatment the existence of the residual heat and edge angle effect on the substrate has changed the composition and microstructure of the coating by raising the fusion temperature and increasing the dilution degree of the coating.展开更多
Based on the nearest surface function formula, a quantitative formula to measure the overlapping degree between the interfacial transition zone (ITZ) of neighboring aggregate particles was put forward. The formula w...Based on the nearest surface function formula, a quantitative formula to measure the overlapping degree between the interfacial transition zone (ITZ) of neighboring aggregate particles was put forward. The formula was further deduced to quantitatively analyze the influence of the volume fraction of aggregate, ITZ thickness and the maximum aggregate diameter on the overlapping degree between neighboring ITZ. The volume of ITZ was quantitatively calculated in actual concrete by comparing the nearest surface function formula with an approximate method, that is the surface area of the aggregates multiplied by the uniform thickness of the ITZ layers. The results showed that the influencing order of these three factors on the overlapping degree between neighboring ITZ in turn was the interface thickness, aggregate volume fraction and the maximum aggregate diameter; As long as the interface thickness 50 μm and the aggregate volume fraction 50%, the calculated error between two methods mentioned above is about 10 %.展开更多
Aluminum alloy 5 A02 with low plasticity was used as target sheet, and stainless steel SUS304 with good plasticity was used as overlapping sheet to investigate the effect of interface friction on bulging formability a...Aluminum alloy 5 A02 with low plasticity was used as target sheet, and stainless steel SUS304 with good plasticity was used as overlapping sheet to investigate the effect of interface friction on bulging formability and microstructure of target sheet in overlapping sheets bulging process. Sheet sliding experiment was performed to measure interface friction coefficient of 5 A02/SUS304 in different lubricating conditions and normal pressure. Overlapping sheets bulging experiment of 5 A02/SUS304 was carried out to investigate the influence of interface friction on limit bulging height, wall thickness distribution, microstructure and fracture morphology of 5 A02 bulging specimens. The results showed that increase of the interface friction coefficient of 5 A02/SUS304 could effectively improve the limit bulging height and deformation uniformity of 5 A02. And the fracture style of 5 A02 transformed from toughness fracture of dimples-micropores gathered to fault slip separation fracture. Therefore, target sheet bulging formability is improved with the increase of interface friction coefficient.展开更多
Clustering is one of the unsupervised learning problems.It is a procedure which partitions data objects into groups.Many algorithms could not overcome the problems of morphology,overlapping and the large number of clu...Clustering is one of the unsupervised learning problems.It is a procedure which partitions data objects into groups.Many algorithms could not overcome the problems of morphology,overlapping and the large number of clusters at the same time.Many scientific communities have used the clustering algorithm from the perspective of density,which is one of the best methods in clustering.This study proposes a density-based spatial clustering of applications with noise(DBSCAN)algorithm based on the selected high-density areas by automatic fuzzy-DBSCAN(AFD)which works with the initialization of two parameters.AFD,by using fuzzy and DBSCAN features,is modeled by the selection of high-density areas and generates two parameters for merging and separating automatically.The two generated parameters provide a state of sub-cluster rules in the Cartesian coordinate system for the dataset.The model overcomes the problems of clustering such as morphology,overlapping,and the number of clusters in a dataset simultaneously.In the experiments,all algorithms are performed on eight data sets with 30 times of running.Three of them are related to overlapping real datasets and the rest are morphologic and synthetic datasets.It is demonstrated that the AFD algorithm outperforms other recently developed clustering algorithms.展开更多
The scattering of plane harmonic P and SV waves by a pair of vertically overlapping lined tunnels buried in an elastic half space is solved using a semi-analytic indirect boundary integration equation method. Then the...The scattering of plane harmonic P and SV waves by a pair of vertically overlapping lined tunnels buried in an elastic half space is solved using a semi-analytic indirect boundary integration equation method. Then the effect of the distance between the two tunnels, the stiffness and density of the lining material, and the incident frequency on the seismic response of the tunnels is investigated. Numerical results demonstrate that the dynamic interaction between the twin tunnels cannot be ignored and the lower tunnel has a significant shielding effect on the upper tunnel for high-frequency incident waves, resulting in great decrease of the dynamic hoop stress in the upper tunnel; for the low-frequency incident waves, in contrast, the lower tunnel can lead to amplification effect on the upper tunnel. It also reveals that the frequency-spectrum characteristics of dynamic stress of the lower tunnel are significantly different from those of the upper tunnel. In addition, for incident P waves in low-frequency region, the soft lining tunnels have significant amplification effect on the surface displacement amplitude, which is slightly larger than that of the corresponding single tunnel.展开更多
In this paper, we present a nonorthogonal overlapping Yee method for solv- ing Maxwell's equations using the diagonal split-cell model. When material interface is presented, the diagonal split-cell model does not req...In this paper, we present a nonorthogonal overlapping Yee method for solv- ing Maxwell's equations using the diagonal split-cell model. When material interface is presented, the diagonal split-cell model does not require permittivity averaging so that better accuracy can be achieved. Our numerical results on optical force computation show that the standard FDTD method converges linearly, while the proposed method achieves quadratic convergence and better accuracy.展开更多
The influenza A viruses have three gene segments, M, NS, and PB1, which code for more than one protein. The overlapping genes from the same segment entail their interdependence, which could be reflected in the evoluti...The influenza A viruses have three gene segments, M, NS, and PB1, which code for more than one protein. The overlapping genes from the same segment entail their interdependence, which could be reflected in the evolutionary constraints, host distinction, and co-mutations of influenza. Most previous studies of overlapping genes focused on their unique evolutionary constraints, and very little was achieved to assess the potential impact of the overlap on other biological aspects of influenza. In this study, our aim was to explore the mutual dependence in host differentiation and co-mutations in M, NS, and PB1 of avian, human, 2009 H1N1, and swine viruses, with Random Forests, information entropy, and mutual information. The host markers and highly co-mutated individual sites and site pairs (P values < 0.035) in the three gene segments were identified with their relative significance between the overlapping genes calculated. Further, Random Forests predicted that among the three stop codons in the current PB1-F2 gene of 2009 H1N1, the significance of a mutation at these sites for host differentiation was, in order from most to least, that at 12, 58, and 88, i.e., the closer to the start of the gene the more important the mutation was. Finally, our sequence analysis surprisingly revealed that the full-length PB1-F2, if the three stop codons were all mutated, would function more as a swine protein than a human protein, although the PB1 of 2009 H1N1 was derived from human H3N2.展开更多
There are currently many approaches to identify the community structure of a network, but relatively few specific to detect overlapping community structures. Likewise, there are few networks with ground truth overlapp...There are currently many approaches to identify the community structure of a network, but relatively few specific to detect overlapping community structures. Likewise, there are few networks with ground truth overlapping nodes. For this reason,we introduce a new network, Pilgrim, with known overlapping nodes, and a new genetic algorithm for detecting such nodes. Pilgrim is comprised of a variety of structures including two communities with dense overlap,which is common in real social structures. This study initially explores the potential of the community detection algorithm LabelRank for consistent overlap detection;however, the deterministic nature of this algorithm restricts it to very few candidate solutions. Therefore, we propose a genetic algorithm using a restricted edge-based clustering technique to detect overlapping communities by maximizing an efficient overlapping modularity function. The proposed restriction to the edge-based representation precludes the possibility of disjoint communities, thereby, dramatically reducing the search space and decreasing the number of generations required to produce an optimal solution. A tunable parameterr allows the strictness of the definition of overlap to be adjusted allowing for refinement in the number of identified overlapping nodes. Our method, tested on several real social networks, yields results comparable to the most effective overlapping community detection algorithms to date.展开更多
Detection of community structures in the complex networks is significant to understand the network structures and analyze the network properties. However, it is still a problem on how to select initial seeds as well a...Detection of community structures in the complex networks is significant to understand the network structures and analyze the network properties. However, it is still a problem on how to select initial seeds as well as to determine the number of communities. In this paper, we proposed the detecting overlapping communities based on vital nodes algorithm(DOCBVA), an algorithm based on vital nodes and initial seeds to detect overlapping communities. First, through some screening method, we find the vital nodes and then the seed communities through the pretreatment of vital nodes. This process differs from most existing methods, and the speed is faster. Then the seeds will be extended. We also adopt a new parameter of attribution degree to extend the seeds and find the overlapping communities. Finally, the remaining nodes that have not been processed in the first two steps will be reprocessed. The number of communities is likely to change until the end of algorithm. The experimental results using some real-world network data and artificial network data are satisfactory and can prove the superiority of the DOCBVA algorithm.展开更多
Overlapping community detection in a network is a challenging issue which attracts lots of attention in recent years.A notion of hesitant node(HN) is proposed. An HN contacts with multiple communities while the comm...Overlapping community detection in a network is a challenging issue which attracts lots of attention in recent years.A notion of hesitant node(HN) is proposed. An HN contacts with multiple communities while the communications are not strong or even accidental, thus the HN holds an implicit community structure.However, HNs are not rare in the real world network. It is important to identify them because they can be efficient hubs which form the overlapping portions of communities or simple attached nodes to some communities. Current approaches have difficulties in identifying and clustering HNs. A density-based rough set model(DBRSM) is proposed by combining the virtue of densitybased algorithms and rough set models. It incorporates the macro perspective of the community structure of the whole network and the micro perspective of the local information held by HNs, which would facilitate the further "growth" of HNs in community. We offer a theoretical support for this model from the point of strength of the trust path. The experiments on the real-world and synthetic datasets show the practical significance of analyzing and clustering the HNs based on DBRSM. Besides, the clustering based on DBRSM promotes the modularity optimization.展开更多
For high reliability and long life systems, system pass/fail data are often rare. Integrating lower-level data, such as data drawn from the subsystem or component pass/fail testing,the Bayesian analysis can improve th...For high reliability and long life systems, system pass/fail data are often rare. Integrating lower-level data, such as data drawn from the subsystem or component pass/fail testing,the Bayesian analysis can improve the precision of the system reliability assessment. If the multi-level pass/fail data are overlapping,one challenging problem for the Bayesian analysis is to develop a likelihood function. Since the computation burden of the existing methods makes them infeasible for multi-component systems, this paper proposes an improved Bayesian approach for the system reliability assessment in light of overlapping data. This approach includes three steps: fristly searching for feasible paths based on the binary decision diagram, then screening feasible points based on space partition and constraint decomposition, and finally simplifying the likelihood function. An example of a satellite rolling control system demonstrates the feasibility and the efficiency of the proposed approach.展开更多
文摘BACKGROUND Gastro-esophageal reflux disease(GERD)may affect the upper digestive tract;up to 20%of population in Western nations are affected by GERD.Antacids,histamine H2-receptor antagonists,and Proton Pump Inhibitors(PPIs)are considered the referring medications for GERD.Nevertheless,PPIs must be managed carefully because their use,especially chronic,could be linked with some adverse effects.An effective and safe alternative pharmacological tool for GERD is needed.After the identification of potentially new medications to flank PPIs,it is mandatory to revise and improve good clinical practices even through a consensus process.AIM To optimize diagnosis and treatment guidelines for GERD through a consensus based on Delphi method.METHODS The availability of clinical studies describing the action of the multicomponent/multitarget medication Nux vomica-Heel,subject of the consensus,is the basic prerequisite for the consensus itself.A modified Delphi process was used to reach a consensus among a panel of Italian GERD specialists on the overlapping approach PPIs/Nux vomica-Heel as a new intervention model for the management of GERD.The Voting Consensus group was composed of 49 Italian Medical Doctors with different specializations:Gastroenterology,otolaryngology,geriatrics,and general medicine.A scientific committee analyzed the literature,determined areas that required investigation(in agreement with the multiple-choice questionnaire results),and identified two topics of interest:(1)GERD disease;and(2)GERD treatment.Statements for each of these topics were then formulated and validated.The Delphi process involved two rounds of questioning submitted to the panel experts using an online platform.RESULTS According to their routinary GERD practice and current clinical evidence,the panel members provided feedback to each questionnaire statement.The experts evaluated 15 statements and reached consensus on all 15.The statements regarding the GERD disease showed high levels of agreement,with consensus ranging from 70%to 92%.The statements regarding the GERD treatment also showed very high levels of agreement,with consensus ranging from 90%to 100%.This Delphi process was able to reach consensus among physicians in relevant aspects of GERD management,such as the adoption of a new approach to treat patients with GERD based on the overlapping between PPIs and Nux vomica-Heel.The consensus was unanimous among the physicians with different specializations,underlying the uniqueness of the agreement reached to identify in the overlapping approach between PPIs and Nux vomica-Heel a new intervention model for GERD management.The results support that an effective approach to deprescribe PPIs through a progressive decalage timetable(reducing PPIs administration to as-needed use),should be considered.CONCLUSION Nux vomica-Heel appears to be a valid opportunity for GERD treatment to favor the deprescription of PPIs and to maintain low disease activity together with the symptomatology remission.
基金supported in part by the Central Government Guides Local Science and TechnologyDevelopment Funds(Grant No.YDZJSX2021A038)in part by theNational Natural Science Foundation of China under(Grant No.61806138)in part by the China University Industry-University-Research Collaborative Innovation Fund(Future Network Innovation Research and Application Project)(Grant 2021FNA04014).
文摘The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.
基金Supported by The Guangxi TCM Suitable Technology Development and Promotion Project,No.GZSY20-20.
文摘BACKGROUND Infections by non-tuberculous mycobacteria(NTM)have become more common in recent years.Mycobacterium canariasense(M.canariasense)was first reported as an opportunistic pathogen in 2004,but there have been very few case reports since then.Nocardia is a genus of aerobic and Gram-positive bacilli,and these species are also opportunistic pathogens and in the Mycobacteriales order.Conventional methods for diagnosis of NTM are inefficient.Metagenomic next-generation sequencing(mNGS)can rapidly detect many pathogenic microorganisms,even rare species.Most NTM and Nocardia infections occur in immunocompromised patients with atypical clinical symptoms.There are no previous reports of infection by M.canariasense and Nocardia farcinica(N.farcinica),especially in immunocompetent patients.This case report describes an immunocompetent 52-year-old woman who had overlapping infections of M.canariasense,N.farcinica,and Candida parapsilosis(C.parapsilosis)based on mNGS.CASE SUMMARY A 52-year-old woman presented with a productive cough and chest pain for 2 wk,and recurrent episodes of moderate-grade fever for 1 wk.She received antibiotics for 1 wk at a local hospital,and experienced defervescence,but the productive cough and chest pain persisted.We collected samples of a lung lesion and alveolar lavage fluid for mNGS.The lung tissue was positive for M.canariasense,N.farcinica,and C.parapsilosis,and the alveolar lavage fluid was positive for M.canariasense.The diagnosis was pneumonia,and application of appropriate antibiotic therapy cured the patient.CONCLUSION Etiological diagnosis is critical for patients with infectious diseases.mNGS can identify rare and novel pathogens,and does not require a priori knowledge.
文摘Since the new curriculum reform,labor education has gradually shed its marginalized position in the“five educations,”and the labor curriculum has become an independent course officially separated from comprehensive practical activity courses.Exploring the practical path of labor curriculum in compulsory education in China has become the primary task of labor education in China.Based on the practical situation of labor curriculum in compulsory education in China,drawing on the theory of overlapping influence domains,and from the perspective of collaborative education among family,school,and community,this paper proposes a curriculum practical path of“school-led”family-school-community collaboration and a curriculum practical path guided by“student-centered”sentiment,in order to provide references for the practice of labor curriculum in compulsory education in China.
文摘There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computing and clustering is introduced to solve the above problems so as to accurately describe the similarity between nodes and fully explore the multi-community structure.A Set Pair Three-Way Overlapping Community Discovery Algorithm for Weighted Social Internet of Things(WSIoT-SPTOCD)is proposed.In the local network structure,which fully considers the topological information between nodes,the set pair connection degree is used to analyze the identity,difference and reverse of neighbor nodes.The similarity degree of different neighbor nodes is defined from network edge weight and node degree,and the similarity measurement method of set pair between nodes based on the local information structure is proposed.According to the number of nodes'neighbors and the connection degree of adjacent edges,the clustering intensity of nodes is defined,and an improved algorithm for initial value selection of k-means is proposed.The nodes are allocated according to the set pair similarity between nodes and different communities.Three-way community structures composed of a positive domain,boundary domain and negative domain are generated iteratively.Next,the overlapping node set is generated according to the calculation results of community node membership.Finally,experiments are carried out on artificial networks and real networks.The results show that WSIoT-SPTOCD performs well in terms of standardized mutual information,overlapping community modularity and F1.
文摘Most modern technologies,such as social media,smart cities,and the internet of things(IoT),rely on big data.When big data is used in the real-world applications,two data challenges such as class overlap and class imbalance arises.When dealing with large datasets,most traditional classifiers are stuck in the local optimum problem.As a result,it’s necessary to look into new methods for dealing with large data collections.Several solutions have been proposed for overcoming this issue.The rapid growth of the available data threatens to limit the usefulness of many traditional methods.Methods such as oversampling and undersampling have shown great promises in addressing the issues of class imbalance.Among all of these techniques,Synthetic Minority Oversampling TechniquE(SMOTE)has produced the best results by generating synthetic samples for the minority class in creating a balanced dataset.The issue is that their practical applicability is restricted to problems involving tens of thousands or lower instances of each.In this paper,we have proposed a parallel mode method using SMOTE and MapReduce strategy,this distributes the operation of the algorithm among a group of computational nodes for addressing the aforementioned problem.Our proposed solution has been divided into three stages.Thefirst stage involves the process of splitting the data into different blocks using a mapping function,followed by a pre-processing step for each mapping block that employs a hybrid SMOTE algo-rithm for solving the class imbalanced problem.On each map block,a decision tree model would be constructed.Finally,the decision tree blocks would be com-bined for creating a classification model.We have used numerous datasets with up to 4 million instances in our experiments for testing the proposed scheme’s cap-abilities.As a result,the Hybrid SMOTE appears to have good scalability within the framework proposed,and it also cuts down the processing time.
文摘This work is concerned with the analysis of blood flow through inclined catheterized arteries having a balloon(angioplasty) with time-variant overlapping stenosis. The nature of blood in small arteries is analyzed mathematically by considering it as a Carreau nanofluid. The highly nonlinear momentum equations of nanofluid model are simplified by considering the mild stenosis case. The formulated problem is solved by a homotopy perturbation expansion in terms of a variant of the Weissenberg number to obtain explicit forms for the axial velocity, the stream function, the pressure gradient, the resistance impedance and the wall shear stress distribution. These solutions depend on the Brownian motion number, thermophoresis number, local temperature Grashof number G_r and local nanoparticle Grash of number B_r. The results were also studied for various values of the physical parameters, such as the Weissenberg number W_i, the power law index n, the taper angle φ, the maximum height of stenosis δ~*, the angle of inclination α, the maximum height of balloon σ~*, the axial displacement of the balloon z_d~*,the flow rate F and the Froud number Fr. The obtained results show that the transmission of axial velocity curves through a Newtonian fluid(Wi=0, n=1, Gr=0, Br=0, Nt=0, Nb≠0) is substantially lower than that through a Carreau nanofluid near the wall of balloon while the inverse occurs in the region between the balloon and stenosis. The streamlines have a clearly distinguished shifting toward the stenotic region and this shifting appears near the wall of the balloon, while it has almost disappeared near the stenotic wall and the trapping bolus in the case of horizontal arteries and Newtonian fluid(Wi=0, n=1, Gr=0, Br=0, Nt=0, Nb≠0) does not appear but for the case of Carreau nanofluid bolus appears.
文摘The finite element method is presented to attain the numerical simulation of the residual stresses field in the material treated by laser shock processing. The distribution of residual stresses generated by a single laser shock with square and round laser spot is predicted and validated by experimental results. With the Finite Element Method (FEM) model, effects of different overlapping rates and impact sequences on the distribution of residual stresses are simulated. The results indicate that: (1) Overlapping laser shock can increase the compressive residual stresses. However, it is not effective on the growth of plastically affected depth; (2) Overlapping rate should be optimized and selected carefully for the large area treatment. Appropriate overlapping rate is beneficial to obtain a homogeneous residual stress field; (3) The impact sequence has a great effect on the residual stress field. It can greatly attenuate the phenomenon of the “residual stress hole” to obtain a homogeneous residual stress field.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61173093 and 61202182)the Postdoctoral Science Foundation of China(Grant No.2012 M521776)+2 种基金the Fundamental Research Funds for the Central Universities of Chinathe Postdoctoral Science Foundation of Shannxi Province,Chinathe Natural Science Basic Research Plan of Shaanxi Province,China(Grant Nos.2013JM8019 and 2014JQ8359)
文摘Community detection is an important methodology for understanding the intrinsic structure and function of a realworld network. In this paper, we propose an effective and efficient algorithm, called Dominant Label Propagation Algorithm(Abbreviated as DLPA), to detect communities in complex networks. The algorithm simulates a special voting process to detect overlapping and non-overlapping community structure in complex networks simultaneously. Our algorithm is very efficient, since its computational complexity is almost linear to the number of edges in the network. Experimental results on both real-world and synthetic networks show that our algorithm also possesses high accuracies on detecting community structure in networks.
文摘The effect of overlapping treatment on microstructure of laser clad WC/Ni60A composite coating was studied with XRD, SEM, TEM and SAED etc. The results show that during the overlapping treatment the existence of the residual heat and edge angle effect on the substrate has changed the composition and microstructure of the coating by raising the fusion temperature and increasing the dilution degree of the coating.
基金Funded by the National Basic Research Program of China (No.2009CB623203)National High-tech R&D Program of China (No.2008AA030794)Postgraduates Research Innovation in University of Jiangsu Province in China (No.CX10B-064Z)
文摘Based on the nearest surface function formula, a quantitative formula to measure the overlapping degree between the interfacial transition zone (ITZ) of neighboring aggregate particles was put forward. The formula was further deduced to quantitatively analyze the influence of the volume fraction of aggregate, ITZ thickness and the maximum aggregate diameter on the overlapping degree between neighboring ITZ. The volume of ITZ was quantitatively calculated in actual concrete by comparing the nearest surface function formula with an approximate method, that is the surface area of the aggregates multiplied by the uniform thickness of the ITZ layers. The results showed that the influencing order of these three factors on the overlapping degree between neighboring ITZ in turn was the interface thickness, aggregate volume fraction and the maximum aggregate diameter; As long as the interface thickness 50 μm and the aggregate volume fraction 50%, the calculated error between two methods mentioned above is about 10 %.
基金Funded by the National Natural Science Foundation of China(No.51575364)the Program for Liaoning Innovation Talents in University(No.LR2017069)the Shenyang Science and Technology Innovation Support Program for Young Talented People(No.RC180189)
文摘Aluminum alloy 5 A02 with low plasticity was used as target sheet, and stainless steel SUS304 with good plasticity was used as overlapping sheet to investigate the effect of interface friction on bulging formability and microstructure of target sheet in overlapping sheets bulging process. Sheet sliding experiment was performed to measure interface friction coefficient of 5 A02/SUS304 in different lubricating conditions and normal pressure. Overlapping sheets bulging experiment of 5 A02/SUS304 was carried out to investigate the influence of interface friction on limit bulging height, wall thickness distribution, microstructure and fracture morphology of 5 A02 bulging specimens. The results showed that increase of the interface friction coefficient of 5 A02/SUS304 could effectively improve the limit bulging height and deformation uniformity of 5 A02. And the fracture style of 5 A02 transformed from toughness fracture of dimples-micropores gathered to fault slip separation fracture. Therefore, target sheet bulging formability is improved with the increase of interface friction coefficient.
文摘Clustering is one of the unsupervised learning problems.It is a procedure which partitions data objects into groups.Many algorithms could not overcome the problems of morphology,overlapping and the large number of clusters at the same time.Many scientific communities have used the clustering algorithm from the perspective of density,which is one of the best methods in clustering.This study proposes a density-based spatial clustering of applications with noise(DBSCAN)algorithm based on the selected high-density areas by automatic fuzzy-DBSCAN(AFD)which works with the initialization of two parameters.AFD,by using fuzzy and DBSCAN features,is modeled by the selection of high-density areas and generates two parameters for merging and separating automatically.The two generated parameters provide a state of sub-cluster rules in the Cartesian coordinate system for the dataset.The model overcomes the problems of clustering such as morphology,overlapping,and the number of clusters in a dataset simultaneously.In the experiments,all algorithms are performed on eight data sets with 30 times of running.Three of them are related to overlapping real datasets and the rest are morphologic and synthetic datasets.It is demonstrated that the AFD algorithm outperforms other recently developed clustering algorithms.
基金supported by the Tianjin Research Program of Application Foundation Advanced Technology (14JCYBJC21900)the National Natural Science Foundation of China under grants 51278327
文摘The scattering of plane harmonic P and SV waves by a pair of vertically overlapping lined tunnels buried in an elastic half space is solved using a semi-analytic indirect boundary integration equation method. Then the effect of the distance between the two tunnels, the stiffness and density of the lining material, and the incident frequency on the seismic response of the tunnels is investigated. Numerical results demonstrate that the dynamic interaction between the twin tunnels cannot be ignored and the lower tunnel has a significant shielding effect on the upper tunnel for high-frequency incident waves, resulting in great decrease of the dynamic hoop stress in the upper tunnel; for the low-frequency incident waves, in contrast, the lower tunnel can lead to amplification effect on the upper tunnel. It also reveals that the frequency-spectrum characteristics of dynamic stress of the lower tunnel are significantly different from those of the upper tunnel. In addition, for incident P waves in low-frequency region, the soft lining tunnels have significant amplification effect on the surface displacement amplitude, which is slightly larger than that of the corresponding single tunnel.
基金supported by the Air Force Office of Scientific Research (AFOSR) under Grant numbers FA9550-04-1-0213 and FA9550-07-1-0010
文摘In this paper, we present a nonorthogonal overlapping Yee method for solv- ing Maxwell's equations using the diagonal split-cell model. When material interface is presented, the diagonal split-cell model does not require permittivity averaging so that better accuracy can be achieved. Our numerical results on optical force computation show that the standard FDTD method converges linearly, while the proposed method achieves quadratic convergence and better accuracy.
文摘The influenza A viruses have three gene segments, M, NS, and PB1, which code for more than one protein. The overlapping genes from the same segment entail their interdependence, which could be reflected in the evolutionary constraints, host distinction, and co-mutations of influenza. Most previous studies of overlapping genes focused on their unique evolutionary constraints, and very little was achieved to assess the potential impact of the overlap on other biological aspects of influenza. In this study, our aim was to explore the mutual dependence in host differentiation and co-mutations in M, NS, and PB1 of avian, human, 2009 H1N1, and swine viruses, with Random Forests, information entropy, and mutual information. The host markers and highly co-mutated individual sites and site pairs (P values < 0.035) in the three gene segments were identified with their relative significance between the overlapping genes calculated. Further, Random Forests predicted that among the three stop codons in the current PB1-F2 gene of 2009 H1N1, the significance of a mutation at these sites for host differentiation was, in order from most to least, that at 12, 58, and 88, i.e., the closer to the start of the gene the more important the mutation was. Finally, our sequence analysis surprisingly revealed that the full-length PB1-F2, if the three stop codons were all mutated, would function more as a swine protein than a human protein, although the PB1 of 2009 H1N1 was derived from human H3N2.
文摘There are currently many approaches to identify the community structure of a network, but relatively few specific to detect overlapping community structures. Likewise, there are few networks with ground truth overlapping nodes. For this reason,we introduce a new network, Pilgrim, with known overlapping nodes, and a new genetic algorithm for detecting such nodes. Pilgrim is comprised of a variety of structures including two communities with dense overlap,which is common in real social structures. This study initially explores the potential of the community detection algorithm LabelRank for consistent overlap detection;however, the deterministic nature of this algorithm restricts it to very few candidate solutions. Therefore, we propose a genetic algorithm using a restricted edge-based clustering technique to detect overlapping communities by maximizing an efficient overlapping modularity function. The proposed restriction to the edge-based representation precludes the possibility of disjoint communities, thereby, dramatically reducing the search space and decreasing the number of generations required to produce an optimal solution. A tunable parameterr allows the strictness of the definition of overlap to be adjusted allowing for refinement in the number of identified overlapping nodes. Our method, tested on several real social networks, yields results comparable to the most effective overlapping community detection algorithms to date.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61672124,61370145,61173183,and 61503375)the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund,China(Grant No.MMJJ20170203)
文摘Detection of community structures in the complex networks is significant to understand the network structures and analyze the network properties. However, it is still a problem on how to select initial seeds as well as to determine the number of communities. In this paper, we proposed the detecting overlapping communities based on vital nodes algorithm(DOCBVA), an algorithm based on vital nodes and initial seeds to detect overlapping communities. First, through some screening method, we find the vital nodes and then the seed communities through the pretreatment of vital nodes. This process differs from most existing methods, and the speed is faster. Then the seeds will be extended. We also adopt a new parameter of attribution degree to extend the seeds and find the overlapping communities. Finally, the remaining nodes that have not been processed in the first two steps will be reprocessed. The number of communities is likely to change until the end of algorithm. The experimental results using some real-world network data and artificial network data are satisfactory and can prove the superiority of the DOCBVA algorithm.
基金supported by the National Natural Science Foundation of China(71271018)
文摘Overlapping community detection in a network is a challenging issue which attracts lots of attention in recent years.A notion of hesitant node(HN) is proposed. An HN contacts with multiple communities while the communications are not strong or even accidental, thus the HN holds an implicit community structure.However, HNs are not rare in the real world network. It is important to identify them because they can be efficient hubs which form the overlapping portions of communities or simple attached nodes to some communities. Current approaches have difficulties in identifying and clustering HNs. A density-based rough set model(DBRSM) is proposed by combining the virtue of densitybased algorithms and rough set models. It incorporates the macro perspective of the community structure of the whole network and the micro perspective of the local information held by HNs, which would facilitate the further "growth" of HNs in community. We offer a theoretical support for this model from the point of strength of the trust path. The experiments on the real-world and synthetic datasets show the practical significance of analyzing and clustering the HNs based on DBRSM. Besides, the clustering based on DBRSM promotes the modularity optimization.
基金supported by the National Natural Science Foundation of China(61304218)
文摘For high reliability and long life systems, system pass/fail data are often rare. Integrating lower-level data, such as data drawn from the subsystem or component pass/fail testing,the Bayesian analysis can improve the precision of the system reliability assessment. If the multi-level pass/fail data are overlapping,one challenging problem for the Bayesian analysis is to develop a likelihood function. Since the computation burden of the existing methods makes them infeasible for multi-component systems, this paper proposes an improved Bayesian approach for the system reliability assessment in light of overlapping data. This approach includes three steps: fristly searching for feasible paths based on the binary decision diagram, then screening feasible points based on space partition and constraint decomposition, and finally simplifying the likelihood function. An example of a satellite rolling control system demonstrates the feasibility and the efficiency of the proposed approach.