The aim of the present study is to contribute to the knowledge about the functioning of the neuronal circuits. We built a mathematical-computational model using graph theory for a complex neurophysiological circuit co...The aim of the present study is to contribute to the knowledge about the functioning of the neuronal circuits. We built a mathematical-computational model using graph theory for a complex neurophysiological circuit consisting </span><span style="font-family:Verdana;">of a reverberating neuronal circuit and a parallel neuronal circuit, which</span><span style="font-family:Verdana;"> could </span><span style="font-family:Verdana;">be coupled. Implementing our model in C++ and applying</span><span style="font-family:Verdana;"> neurophysiological values found in the literature, we studied the discharge pattern of the reverberant circuit and the parallel circuit separately for the same input signal pattern, examining the influence of the refractory period and the synaptic delay on the respective output signal patterns. Then, the same study was performed for the complete circuit, in which the two circuits were coupled, and the parallel circuit could then influence the functioning of the reverberant. The results showed that the refractory period played an important role in forming the pattern of the output spectrum of a reverberating circuit. The inhibitory action of the parallel circuit was able to regulate the reverberation frequency, suggesting that parallel circuits may be involved in the control of reverberation circuits related to motive activities underlying precision tasks and perhaps underlying neural work processes and immediate memories.展开更多
Unsupervised neural networks such as the Kohonen Self-Organizing Maps （SOM） have been widely used for searching natural clusters in multidimensional and massive data. One example where the data available for analysi...Unsupervised neural networks such as the Kohonen Self-Organizing Maps （SOM） have been widely used for searching natural clusters in multidimensional and massive data. One example where the data available for analysis can be extremely large is seismic interpretation for hydrocarbon exploration. In order to assist the interpreter in identifying characteristics of interest confined in the seismic data, the authors present a set of data attributes that can be used to train a SOM in such a way that zones of interest can be automatically identified or segmented, reducing time in the interpretation process. The authors show how to associate SOM to 2D color maps to visually identify the clustering structure of the input seismic data, and apply the proposed technique to a 2D synthetic seismic dataset of salt structures.展开更多
In this work, we consider a homotopic principle for solving large-scale and dense l1underdetermined problems and its applications in image processing and classification. We solve the face recognition problem where the...In this work, we consider a homotopic principle for solving large-scale and dense l1underdetermined problems and its applications in image processing and classification. We solve the face recognition problem where the input image contains corrupted and/or lost pixels. The approach involves two steps: first, the incomplete or corrupted image is subject to an inpainting process, and secondly, the restored image is used to carry out the classification or recognition task. Addressing these two steps involves solving large scale l1minimization problems. To that end, we propose to solve a sequence of linear equality constrained multiquadric problems that depends on a regularization parameter that converges to zero. The procedure generates a central path that converges to a point on the solution set of the l1underdetermined problem. In order to solve each subproblem, a conjugate gradient algorithm is formulated. When noise is present in the model, inexact directions are taken so that an approximate solution is computed faster. This prevents the ill conditioning produced when the conjugate gradient is required to iterate until a zero residual is attained.展开更多
In recent years,as China has grappled with rising debt and broad economic restructure,the prevalence of zombie firms has become a critical problem.This paper provides a theoretical framework illustrating the rationale...In recent years,as China has grappled with rising debt and broad economic restructure,the prevalence of zombie firms has become a critical problem.This paper provides a theoretical framework illustrating the rationale behind the occurrence of zombie firms from the perspective of banks.We develop differential equations to model a bank s expectation and the ex ante estimate that underlies its decision to refinance an insolvent borrower.An optimistic expectation is essential in zombie lending and is intrinsic to the countercyclical pattern of zombie firms.Our model also predicts that debt can build up to an unsustainable level if recovery ofprofitability is sluggish or the initial debt burden is too high.Examining the Chinese experience of zombie firms over 2007-2017,this paper highlights two findings.First,the share of zombie firms among Shanghai and Shenzhen A-share listed companies demonstrates a countercyclical pattern.Second,the positive correlation between zombie share and debt accumulation across manufacturing sectors sheds light on the link between zombie firms and the rising corporate debt in China.To deal with the zombie"problem,the government should carefully weigh its policies to avoid further distortions because the occurrence of zombie firms may be inevitable and impossible to eliminate.展开更多
Controlled C-N configurations,i.e.,pyrrolic-N,pyridinic-N,and graphitic-N,are promising strategies to tailor the carbon dots’(CDs)optical properties into the first near infrared(NIR)window(650-900 nm),a responsive ra...Controlled C-N configurations,i.e.,pyrrolic-N,pyridinic-N,and graphitic-N,are promising strategies to tailor the carbon dots’(CDs)optical properties into the first near infrared(NIR)window(650-900 nm),a responsive range for biomedical application.However,a deep understanding of the role of the C-N configuration in the CDs’properties is still challenging and thoughtprovoking owing to their complex structure.Here,an underlying pyrrolic-N concentration and position effect on the pyrrolic-N-rich CDs’absorption was comprehensively elucidated based on the integrated experimental and computational studies.The assynthesized pyrrolic-N-rich CDs exhibit a first NIR window absorption centered at 650 nm with high photothermal conversion.Pyrrolic-N concentrations from 1.4%to 11.3%and positions(edge and mid-site)were systematically investigated.A mid-site pyrrolic-N was subsequently generated after the pyrrolic-N concentration more than 10%.Edge-site pyrrolic-N induces a frontier orbital hybridization,reducing bandgap energy,while mid-site pyrrolic-N plays a critical role in inducing a first NIR window absorption owing to their high charge transfer.Also,pyrrolic-N-rich CDs inherit a bowl-like topological feature,elevating the CDs’layer thickness as much as 0.71 nm.This study shed light on the design and optimization of pyrrolic-N on CDs for the first NIR window responsive materials in any biomedical application.展开更多
文摘The aim of the present study is to contribute to the knowledge about the functioning of the neuronal circuits. We built a mathematical-computational model using graph theory for a complex neurophysiological circuit consisting </span><span style="font-family:Verdana;">of a reverberating neuronal circuit and a parallel neuronal circuit, which</span><span style="font-family:Verdana;"> could </span><span style="font-family:Verdana;">be coupled. Implementing our model in C++ and applying</span><span style="font-family:Verdana;"> neurophysiological values found in the literature, we studied the discharge pattern of the reverberant circuit and the parallel circuit separately for the same input signal pattern, examining the influence of the refractory period and the synaptic delay on the respective output signal patterns. Then, the same study was performed for the complete circuit, in which the two circuits were coupled, and the parallel circuit could then influence the functioning of the reverberant. The results showed that the refractory period played an important role in forming the pattern of the output spectrum of a reverberating circuit. The inhibitory action of the parallel circuit was able to regulate the reverberation frequency, suggesting that parallel circuits may be involved in the control of reverberation circuits related to motive activities underlying precision tasks and perhaps underlying neural work processes and immediate memories.
文摘Unsupervised neural networks such as the Kohonen Self-Organizing Maps （SOM） have been widely used for searching natural clusters in multidimensional and massive data. One example where the data available for analysis can be extremely large is seismic interpretation for hydrocarbon exploration. In order to assist the interpreter in identifying characteristics of interest confined in the seismic data, the authors present a set of data attributes that can be used to train a SOM in such a way that zones of interest can be automatically identified or segmented, reducing time in the interpretation process. The authors show how to associate SOM to 2D color maps to visually identify the clustering structure of the input seismic data, and apply the proposed technique to a 2D synthetic seismic dataset of salt structures.
文摘In this work, we consider a homotopic principle for solving large-scale and dense l1underdetermined problems and its applications in image processing and classification. We solve the face recognition problem where the input image contains corrupted and/or lost pixels. The approach involves two steps: first, the incomplete or corrupted image is subject to an inpainting process, and secondly, the restored image is used to carry out the classification or recognition task. Addressing these two steps involves solving large scale l1minimization problems. To that end, we propose to solve a sequence of linear equality constrained multiquadric problems that depends on a regularization parameter that converges to zero. The procedure generates a central path that converges to a point on the solution set of the l1underdetermined problem. In order to solve each subproblem, a conjugate gradient algorithm is formulated. When noise is present in the model, inexact directions are taken so that an approximate solution is computed faster. This prevents the ill conditioning produced when the conjugate gradient is required to iterate until a zero residual is attained.
文摘In recent years,as China has grappled with rising debt and broad economic restructure,the prevalence of zombie firms has become a critical problem.This paper provides a theoretical framework illustrating the rationale behind the occurrence of zombie firms from the perspective of banks.We develop differential equations to model a bank s expectation and the ex ante estimate that underlies its decision to refinance an insolvent borrower.An optimistic expectation is essential in zombie lending and is intrinsic to the countercyclical pattern of zombie firms.Our model also predicts that debt can build up to an unsustainable level if recovery ofprofitability is sluggish or the initial debt burden is too high.Examining the Chinese experience of zombie firms over 2007-2017,this paper highlights two findings.First,the share of zombie firms among Shanghai and Shenzhen A-share listed companies demonstrates a countercyclical pattern.Second,the positive correlation between zombie share and debt accumulation across manufacturing sectors sheds light on the link between zombie firms and the rising corporate debt in China.To deal with the zombie"problem,the government should carefully weigh its policies to avoid further distortions because the occurrence of zombie firms may be inevitable and impossible to eliminate.
基金This work was fully supported by the Indonesian Endowment Fund for Education and the Indonesian Science Fund through the International Collaboration RISPRO Funding Program(No.RISPRO/KI/B1/KOM/11/4542/2/2020).
文摘Controlled C-N configurations,i.e.,pyrrolic-N,pyridinic-N,and graphitic-N,are promising strategies to tailor the carbon dots’(CDs)optical properties into the first near infrared(NIR)window(650-900 nm),a responsive range for biomedical application.However,a deep understanding of the role of the C-N configuration in the CDs’properties is still challenging and thoughtprovoking owing to their complex structure.Here,an underlying pyrrolic-N concentration and position effect on the pyrrolic-N-rich CDs’absorption was comprehensively elucidated based on the integrated experimental and computational studies.The assynthesized pyrrolic-N-rich CDs exhibit a first NIR window absorption centered at 650 nm with high photothermal conversion.Pyrrolic-N concentrations from 1.4%to 11.3%and positions(edge and mid-site)were systematically investigated.A mid-site pyrrolic-N was subsequently generated after the pyrrolic-N concentration more than 10%.Edge-site pyrrolic-N induces a frontier orbital hybridization,reducing bandgap energy,while mid-site pyrrolic-N plays a critical role in inducing a first NIR window absorption owing to their high charge transfer.Also,pyrrolic-N-rich CDs inherit a bowl-like topological feature,elevating the CDs’layer thickness as much as 0.71 nm.This study shed light on the design and optimization of pyrrolic-N on CDs for the first NIR window responsive materials in any biomedical application.
