We propose the Dantzig selector based on the l_(1-q)(1<q≤2)minimization model for the sparse signal recovery.First,we discuss some properties of l_(1-q)minimization model and give some useful inequalities.Then,we ...We propose the Dantzig selector based on the l_(1-q)(1<q≤2)minimization model for the sparse signal recovery.First,we discuss some properties of l_(1-q)minimization model and give some useful inequalities.Then,we give a sufficient condition based on the restricted isometry property for the stable recovery of signals.The l_(1-2)minimization model of Yin-Lou-He is extended to the l_(1-q)minimization model.展开更多
Municipal solid waste generation is strongly linked to rising human population and expanding urban areas, with significant implications on urban metabolism as well as space and place values redefinition. Effective man...Municipal solid waste generation is strongly linked to rising human population and expanding urban areas, with significant implications on urban metabolism as well as space and place values redefinition. Effective management performance of municipal solid waste management underscores the interdisciplinarity strategies. Such knowledge and skills are paramount to uncover the sources of waste generation as well as means of waste storage, collection, recycling, transportation, handling/treatment, disposal, and monitoring. This study was conducted in Dar es Salaam city. Driven by the curiosity model of the solid waste minimization performance at source, study data was collected using focus group discussion techniques to ward-level local government officers, which was triangulated with literature and documentary review. The main themes of the FGD were situational factors (SFA) and local government by-laws (LGBY). In the FGD session, sub-themes of SFA tricked to understand how MSW minimization is related to the presence and effect of services such as land use planning, availability of landfills, solid waste transfer stations, material recovery facilities, incinerators, solid waste collection bins, solid waste trucks, solid waste management budget and solid waste collection agents. Similarly, FGD on LGBY was extended by sub-themes such as contents of the by-law, community awareness of the by-law, and by-law enforcement mechanisms. While data preparation applied an analytical hierarchy process, data analysis applied an ordinary least square (OLS) regression model for sub-criteria that explain SFA and LGBY;and OLS standard residues as variables into geographically weighted regression with a resolution of 241 × 241 meter in ArcMap v10.5. Results showed that situational factors and local government by-laws have a strong relationship with the rate of minimizing solid waste dumping in water bodies (local R square = 0.94).展开更多
Puncturing has been recognized as a promising technology to cope with the coexistence problem of enhanced mobile broadband(eMBB) and ultra-reliable low latency communications(URLLC)traffic. However, the steady perform...Puncturing has been recognized as a promising technology to cope with the coexistence problem of enhanced mobile broadband(eMBB) and ultra-reliable low latency communications(URLLC)traffic. However, the steady performance of eMBB traffic while meeting the requirements of URLLC traffic with puncturing is a major challenge in some realistic scenarios. In this paper, we pay attention to the timely and energy-efficient processing for eMBB traffic in the industrial Internet of Things(IIoT), where mobile edge computing(MEC) is employed for data processing. Specifically, the performance of eMBB traffic and URLLC traffic in a MEC-based IIoT system is ensured by setting the threshold of tolerable delay and outage probability, respectively. Furthermore,considering the limited energy supply, an energy minimization problem of eMBB device is formulated under the above constraints, by jointly optimizing the resource blocks(RBs) punctured by URLLC traffic, data offloading and transmit power of eMBB device. With Markov's inequality, the problem is reformulated by transforming the probabilistic outage constraint into a deterministic constraint. Meanwhile, an iterative energy minimization algorithm(IEMA) is proposed.Simulation results demonstrate that our algorithm has a significant reduction in the energy consumption for eMBB device and achieves a better overall effect compared to several benchmarks.展开更多
Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transfo...Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transform domain, we can improve the accuracy and stability of the reconstruction by transforming it to a sparse optimization problem. In this paper, we propose a mathematical model for the sparse reconstruction of data based on the LO-norm minimization. Furthermore, we discuss two types of the approximation algorithm for the LO- norm minimization according to the size and characteristics of the geophysical data： namely, the iteratively reweighted least-squares algorithm and the fast iterative hard thresholding algorithm. Theoretical and numerical analysis showed that applying the iteratively reweighted least-squares algorithm to the reconstruction of potential field data exploits its fast convergence rate, short calculation time, and high precision, whereas the fast iterative hard thresholding algorithm is more suitable for processing seismic data, moreover, its computational efficiency is better than that of the traditional iterative hard thresholding algorithm.展开更多
With the entropy generation minimization （EGM） method, the thermodynamical performance optimization in a thermoelectric refrigeration system is studied. The optimization is affected by the irreversibility of heat tr...With the entropy generation minimization （EGM） method, the thermodynamical performance optimization in a thermoelectric refrigeration system is studied. The optimization is affected by the irreversibility of heat transfer caused by finite temperature differences, the heat leak between external heat reservoirs and the internal dissipation of working fluids. EGM is taken as an objective function for the optimization. The objective function and design parameters are obtained. Optimal performance curves are presented by thermal and electronic parameters. Effects of these parameters on general and optimal performances are investigated. Results are helpful in determining optimal design conditions in real thermoelectric refrigeration systems.展开更多
BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery ...BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery and long-term survival.Accurate preoperative identification of high-risk patients is critical for improving outcomes.AIM To establish and validate a risk prediction and stratification model for the risk of SAEs in patients with MIE.METHODS This retrospective study included 747 patients who underwent MIE at two centers from January 2019 to February 2024.Patients were separated into a train set(n=549)and a validation set(n=198).After screening by least absolute shrinkage and selection operator regression,multivariate logistic regression analyzed clinical and intraoperative variables to identify independent risk factors for SAEs.A risk stratification model was constructed and validated to predict the probability of SAEs.RESULTS SAEs occurred in 10.2%of patients in train set and 13.6%in the validation set.Patients with SAE had significantly higher complication rate and a longer hospital stay after surgery.The key independent risk factors identified included chronic obstructive pulmonary disease,a history of alcohol consumption,low forced expiratory volume in the first second,and low albumin levels.The stratification model has excellent prediction accuracy,with an area under the curve of 0.889 for the training set and an area under the curve of 0.793 for the validation set.CONCLUSION The developed risk stratification model effectively predicts the risk of SAEs in patients undergoing MIE,facilitating targeted preoperative interventions and improving perioperative management.展开更多
基金supported by the National Natural Science Foundation of China“Variable exponential function spaces on variable anisotropic Euclidean spaces and their applications”(12261083),“Harmonic analysis on affine symmetric spaces”(12161083).
文摘We propose the Dantzig selector based on the l_(1-q)(1<q≤2)minimization model for the sparse signal recovery.First,we discuss some properties of l_(1-q)minimization model and give some useful inequalities.Then,we give a sufficient condition based on the restricted isometry property for the stable recovery of signals.The l_(1-2)minimization model of Yin-Lou-He is extended to the l_(1-q)minimization model.
文摘Municipal solid waste generation is strongly linked to rising human population and expanding urban areas, with significant implications on urban metabolism as well as space and place values redefinition. Effective management performance of municipal solid waste management underscores the interdisciplinarity strategies. Such knowledge and skills are paramount to uncover the sources of waste generation as well as means of waste storage, collection, recycling, transportation, handling/treatment, disposal, and monitoring. This study was conducted in Dar es Salaam city. Driven by the curiosity model of the solid waste minimization performance at source, study data was collected using focus group discussion techniques to ward-level local government officers, which was triangulated with literature and documentary review. The main themes of the FGD were situational factors (SFA) and local government by-laws (LGBY). In the FGD session, sub-themes of SFA tricked to understand how MSW minimization is related to the presence and effect of services such as land use planning, availability of landfills, solid waste transfer stations, material recovery facilities, incinerators, solid waste collection bins, solid waste trucks, solid waste management budget and solid waste collection agents. Similarly, FGD on LGBY was extended by sub-themes such as contents of the by-law, community awareness of the by-law, and by-law enforcement mechanisms. While data preparation applied an analytical hierarchy process, data analysis applied an ordinary least square (OLS) regression model for sub-criteria that explain SFA and LGBY;and OLS standard residues as variables into geographically weighted regression with a resolution of 241 × 241 meter in ArcMap v10.5. Results showed that situational factors and local government by-laws have a strong relationship with the rate of minimizing solid waste dumping in water bodies (local R square = 0.94).
基金supported by the Natural Science Foundation of China (No.62171051)。
文摘Puncturing has been recognized as a promising technology to cope with the coexistence problem of enhanced mobile broadband(eMBB) and ultra-reliable low latency communications(URLLC)traffic. However, the steady performance of eMBB traffic while meeting the requirements of URLLC traffic with puncturing is a major challenge in some realistic scenarios. In this paper, we pay attention to the timely and energy-efficient processing for eMBB traffic in the industrial Internet of Things(IIoT), where mobile edge computing(MEC) is employed for data processing. Specifically, the performance of eMBB traffic and URLLC traffic in a MEC-based IIoT system is ensured by setting the threshold of tolerable delay and outage probability, respectively. Furthermore,considering the limited energy supply, an energy minimization problem of eMBB device is formulated under the above constraints, by jointly optimizing the resource blocks(RBs) punctured by URLLC traffic, data offloading and transmit power of eMBB device. With Markov's inequality, the problem is reformulated by transforming the probabilistic outage constraint into a deterministic constraint. Meanwhile, an iterative energy minimization algorithm(IEMA) is proposed.Simulation results demonstrate that our algorithm has a significant reduction in the energy consumption for eMBB device and achieves a better overall effect compared to several benchmarks.
基金supported by the National Natural Science Foundation of China (Grant No.41074133)
文摘Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transform domain, we can improve the accuracy and stability of the reconstruction by transforming it to a sparse optimization problem. In this paper, we propose a mathematical model for the sparse reconstruction of data based on the LO-norm minimization. Furthermore, we discuss two types of the approximation algorithm for the LO- norm minimization according to the size and characteristics of the geophysical data： namely, the iteratively reweighted least-squares algorithm and the fast iterative hard thresholding algorithm. Theoretical and numerical analysis showed that applying the iteratively reweighted least-squares algorithm to the reconstruction of potential field data exploits its fast convergence rate, short calculation time, and high precision, whereas the fast iterative hard thresholding algorithm is more suitable for processing seismic data, moreover, its computational efficiency is better than that of the traditional iterative hard thresholding algorithm.
文摘With the entropy generation minimization （EGM） method, the thermodynamical performance optimization in a thermoelectric refrigeration system is studied. The optimization is affected by the irreversibility of heat transfer caused by finite temperature differences, the heat leak between external heat reservoirs and the internal dissipation of working fluids. EGM is taken as an objective function for the optimization. The objective function and design parameters are obtained. Optimal performance curves are presented by thermal and electronic parameters. Effects of these parameters on general and optimal performances are investigated. Results are helpful in determining optimal design conditions in real thermoelectric refrigeration systems.
基金Supported by Joint Funds for the Innovation of Science and Technology,Fujian Province,No.2023Y9187 and No.2021Y9057.
文摘BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery and long-term survival.Accurate preoperative identification of high-risk patients is critical for improving outcomes.AIM To establish and validate a risk prediction and stratification model for the risk of SAEs in patients with MIE.METHODS This retrospective study included 747 patients who underwent MIE at two centers from January 2019 to February 2024.Patients were separated into a train set(n=549)and a validation set(n=198).After screening by least absolute shrinkage and selection operator regression,multivariate logistic regression analyzed clinical and intraoperative variables to identify independent risk factors for SAEs.A risk stratification model was constructed and validated to predict the probability of SAEs.RESULTS SAEs occurred in 10.2%of patients in train set and 13.6%in the validation set.Patients with SAE had significantly higher complication rate and a longer hospital stay after surgery.The key independent risk factors identified included chronic obstructive pulmonary disease,a history of alcohol consumption,low forced expiratory volume in the first second,and low albumin levels.The stratification model has excellent prediction accuracy,with an area under the curve of 0.889 for the training set and an area under the curve of 0.793 for the validation set.CONCLUSION The developed risk stratification model effectively predicts the risk of SAEs in patients undergoing MIE,facilitating targeted preoperative interventions and improving perioperative management.
