This paper explores whether the level of stock price informativeness about listed companies’future earnings is influenced by investor sentiment.In prior studies,investor sentiment,which can be regarded as the mood of...This paper explores whether the level of stock price informativeness about listed companies’future earnings is influenced by investor sentiment.In prior studies,investor sentiment,which can be regarded as the mood of the market,is defined as a belief about unjustified firms’future cash flow,investment returns and risks in capital markets.At the same time,stock price informativeness indicates how much information about a firm’s future earnings is reflected by stock prices.Higher price informativeness indicates a higher market efficiency level.Using linear regression analysis based on panel data from China’s stock market and listed companies,this research documents how stock price informativeness can be reduced by investor sentiment during market pessimism.However,although the explanatory power of future earnings over stock returns is strengthened by positive sentiment,it is not certain that positive sentiment increases price informativeness since the asset price bubble exists with extreme market optimism.Furthermore,the effect of sentiment on price informativeness would be weakened by higher state-owned shareholding.These empirical results imply that sentiment,to a certain degree,causes the investors’ignorance during pessimism and exaggeration during optimism over firms’earning prospects.Moreover,investors usually lack favour for state-owned enterprises during optimism,even though these companies actually have considerable earning prospects.While during pessimism,which usually happens after a crisis,the profitability and reliability of these state-owned enterprises are again emphasised by investors.展开更多
It is noted that necessity of further increase of accuracy of GPS positioning systems requires de-velopment of more perfect methods to compensate information losses occurred due to residual ionospheric delay by using ...It is noted that necessity of further increase of accuracy of GPS positioning systems requires de-velopment of more perfect methods to compensate information losses occurred due to residual ionospheric delay by using optimization procedures. According to the conditions of formulated optimization task, the signal/noise ratio in measurements of zenith wet delay depends on the second order ionospheric errors, geographic latitude and day of year. At the same time if we assume that the number of measurements at the fixed geographic site is proportional to geographic latitude and if we accept existence of only two antiphase scenarios for variation of residual ionospheric delay on latitude normed by their specific constant, there should be optimum functional dependence of precipitated water on latitude upon which the quantity of measuring information reaches the maximum. The mathematical grounding of solution of formulated optimization task is given.展开更多
This study examines the impact of employee stock ownership plans(ESOPs)on stock-price informativeness in Chinese stock markets.Its findings indicate that firms implementing ESOPs experienced an average 11.89 percent i...This study examines the impact of employee stock ownership plans(ESOPs)on stock-price informativeness in Chinese stock markets.Its findings indicate that firms implementing ESOPs experienced an average 11.89 percent increase in stock-price informativeness.The plans improved stock-price informativeness through increased external attention and supervision.An event study shows that ESOPs gave rise to an announcement effect,driven by anticipated performance improvements and the novelty associated with ESOPs.A mechanism analysis demonstrates that the implementation of ESOPs attracted market attention,and the increased market supervision resulting from this mitigated the moral hazards of management associated with ESOPs.Plans with more positive signals exerted a greater influence.Notably,ESOPs that prioritized management incentives gained more recognition in the market.As the incentive effects of ESOPs were weaker than those of equity incentive plans and the ESOPs lost novelty over time,the annual announcement effect diminished gradually.These findings underscore the necessity of strengthening ESOP incentives for continued optimization of priceefficiency.展开更多
Research on biogeographical ancestry(BGA)is becoming of growing interest in forensic genetics and in the biomedical literature(1)Thus,for instance,the need to predict ethnicity of an unknown suspect based on DNA profi...Research on biogeographical ancestry(BGA)is becoming of growing interest in forensic genetics and in the biomedical literature(1)Thus,for instance,the need to predict ethnicity of an unknown suspect based on DNA profiles found at the crime scene is of maximum interest in criminalistics[2],and several autosomal SNP panels have been designed and tested for BGA investigations[3,4].Most of these panels aim at discriminating three main continental groups(sub-Saharan Africans,Europeans,and Asians)by way of testing a number of ancestry informative markers(AIMs)that run from a few dozens to a few hundred[5](see more background in Supplementary data online).展开更多
Traffic sign detection is a critical component of driving systems.Single-stage network-based traffic sign detection algorithms,renowned for their fast detection speeds and high accuracy,have become the dominant approa...Traffic sign detection is a critical component of driving systems.Single-stage network-based traffic sign detection algorithms,renowned for their fast detection speeds and high accuracy,have become the dominant approach in current practices.However,in complex and dynamic traffic scenes,particularly with smaller traffic sign objects,challenges such as missed and false detections can lead to reduced overall detection accuracy.To address this issue,this paper proposes a detection algorithm that integrates edge and shape information.Recognizing that traffic signs have specific shapes and distinct edge contours,this paper introduces an edge feature extraction branch within the backbone network,enabling adaptive fusion with features of the same hierarchical level.Additionally,a shape prior convolution module is designed to replaces the first two convolutional modules of the backbone network,aimed at enhancing the model's perception ability for specific shape objects and reducing its sensitivity to background noise.The algorithm was evaluated on the CCTSDB and TT100k datasets,and compared to YOLOv8s,the mAP50 values increased by 3.0%and 10.4%,respectively,demonstrating the effectiveness of the proposed method in improving the accuracy of traffic sign detection.展开更多
Experimental therapies targeting immune and stromal cells,such as mast cells,cancer-associated fibroblasts,dendritic cells,and tumor endothelial cells,in the treatment of gastrointestinal solid tumors pose new and com...Experimental therapies targeting immune and stromal cells,such as mast cells,cancer-associated fibroblasts,dendritic cells,and tumor endothelial cells,in the treatment of gastrointestinal solid tumors pose new and complex surgical and medico-legal challenges.These innovative treatments require that informed consent not be limited to simple acceptance of the medical procedure,but instead reflect a true relational and cognitive process grounded in understanding,free choice,and the ability to revoke consent at any time.In particular,it is essential that the patient understands the experimental nature of the therapy,its development stage,potential benefits and risks,as well as the implications for their health and personal dignity.In the case of stromal cell-based treatments,which may exert complex immunomodulatory effects or activate angiogenic pathways that are not yet fully understood,patients must be made fully aware that they are participating in a non-standardized therapy whose outcomes,whether beneficial or harmful,cannot yet be predicted with certainty.This requires particularly careful medical communication,using simple yet scientifically accurate explanations delivered in appropriate language,along with a final verification of the patient’s actual understanding.展开更多
Quantitative analysis of aluminum-silicon(Al-Si)alloy microstructure is crucial for evaluating and controlling alloy performance.Conventional analysis methods rely on manual segmentation,which is inefficient and subje...Quantitative analysis of aluminum-silicon(Al-Si)alloy microstructure is crucial for evaluating and controlling alloy performance.Conventional analysis methods rely on manual segmentation,which is inefficient and subjective,while fully supervised deep learning approaches require extensive and expensive pixel-level annotated data.Furthermore,existing semi-supervised methods still face challenges in handling the adhesion of adjacent primary silicon particles and effectively utilizing consistency in unlabeled data.To address these issues,this paper proposes a novel semi-supervised framework for Al-Si alloy microstructure image segmentation.First,we introduce a Rotational Uncertainty Correction Strategy(RUCS).This strategy employs multi-angle rotational perturbations andMonte Carlo sampling to assess prediction consistency,generating a pixel-wise confidence weight map.By integrating this map into the loss function,the model dynamically focuses on high-confidence regions,thereby improving generalization ability while reducing manual annotation pressure.Second,we design a Boundary EnhancementModule(BEM)to strengthen boundary feature extraction through erosion difference and multi-scale dilated convolutions.This module guides the model to focus on the boundary regions of adjacent particles,effectively resolving particle adhesion and improving segmentation accuracy.Systematic experiments were conducted on the Aluminum-Silicon Alloy Microstructure Dataset(ASAD).Results indicate that the proposed method performs exceptionally well with scarce labeled data.Specifically,using only 5%labeled data,our method improves the Jaccard index and Adjusted Rand Index(ARI)by 2.84 and 1.57 percentage points,respectively,and reduces the Variation of Information(VI)by 8.65 compared to stateof-the-art semi-supervised models,approaching the performance levels of 10%labeled data.These results demonstrate that the proposed method significantly enhances the accuracy and robustness of quantitative microstructure analysis while reducing annotation costs.展开更多
文摘This paper explores whether the level of stock price informativeness about listed companies’future earnings is influenced by investor sentiment.In prior studies,investor sentiment,which can be regarded as the mood of the market,is defined as a belief about unjustified firms’future cash flow,investment returns and risks in capital markets.At the same time,stock price informativeness indicates how much information about a firm’s future earnings is reflected by stock prices.Higher price informativeness indicates a higher market efficiency level.Using linear regression analysis based on panel data from China’s stock market and listed companies,this research documents how stock price informativeness can be reduced by investor sentiment during market pessimism.However,although the explanatory power of future earnings over stock returns is strengthened by positive sentiment,it is not certain that positive sentiment increases price informativeness since the asset price bubble exists with extreme market optimism.Furthermore,the effect of sentiment on price informativeness would be weakened by higher state-owned shareholding.These empirical results imply that sentiment,to a certain degree,causes the investors’ignorance during pessimism and exaggeration during optimism over firms’earning prospects.Moreover,investors usually lack favour for state-owned enterprises during optimism,even though these companies actually have considerable earning prospects.While during pessimism,which usually happens after a crisis,the profitability and reliability of these state-owned enterprises are again emphasised by investors.
文摘It is noted that necessity of further increase of accuracy of GPS positioning systems requires de-velopment of more perfect methods to compensate information losses occurred due to residual ionospheric delay by using optimization procedures. According to the conditions of formulated optimization task, the signal/noise ratio in measurements of zenith wet delay depends on the second order ionospheric errors, geographic latitude and day of year. At the same time if we assume that the number of measurements at the fixed geographic site is proportional to geographic latitude and if we accept existence of only two antiphase scenarios for variation of residual ionospheric delay on latitude normed by their specific constant, there should be optimum functional dependence of precipitated water on latitude upon which the quantity of measuring information reaches the maximum. The mathematical grounding of solution of formulated optimization task is given.
基金support from the National Social Science Fund of China(No.21BJY079).
文摘This study examines the impact of employee stock ownership plans(ESOPs)on stock-price informativeness in Chinese stock markets.Its findings indicate that firms implementing ESOPs experienced an average 11.89 percent increase in stock-price informativeness.The plans improved stock-price informativeness through increased external attention and supervision.An event study shows that ESOPs gave rise to an announcement effect,driven by anticipated performance improvements and the novelty associated with ESOPs.A mechanism analysis demonstrates that the implementation of ESOPs attracted market attention,and the increased market supervision resulting from this mitigated the moral hazards of management associated with ESOPs.Plans with more positive signals exerted a greater influence.Notably,ESOPs that prioritized management incentives gained more recognition in the market.As the incentive effects of ESOPs were weaker than those of equity incentive plans and the ESOPs lost novelty over time,the annual announcement effect diminished gradually.These findings underscore the necessity of strengthening ESOP incentives for continued optimization of priceefficiency.
基金support from the project Ge PEM ISCIII/PI16/01478/Cofinanciado FEDER of the Instituto de Salud Carlos IIIsupport from project Re SVinext ISCIII/PI16/01569/Cofinanciado FEDER
文摘Research on biogeographical ancestry(BGA)is becoming of growing interest in forensic genetics and in the biomedical literature(1)Thus,for instance,the need to predict ethnicity of an unknown suspect based on DNA profiles found at the crime scene is of maximum interest in criminalistics[2],and several autosomal SNP panels have been designed and tested for BGA investigations[3,4].Most of these panels aim at discriminating three main continental groups(sub-Saharan Africans,Europeans,and Asians)by way of testing a number of ancestry informative markers(AIMs)that run from a few dozens to a few hundred[5](see more background in Supplementary data online).
基金supported by the National Natural Science Foundation of China(Grant Nos.62572057,62272049,U24A20331)Beijing Natural Science Foundation(Grant Nos.4232026,4242020)Academic Research Projects of Beijing Union University(Grant No.ZK10202404).
文摘Traffic sign detection is a critical component of driving systems.Single-stage network-based traffic sign detection algorithms,renowned for their fast detection speeds and high accuracy,have become the dominant approach in current practices.However,in complex and dynamic traffic scenes,particularly with smaller traffic sign objects,challenges such as missed and false detections can lead to reduced overall detection accuracy.To address this issue,this paper proposes a detection algorithm that integrates edge and shape information.Recognizing that traffic signs have specific shapes and distinct edge contours,this paper introduces an edge feature extraction branch within the backbone network,enabling adaptive fusion with features of the same hierarchical level.Additionally,a shape prior convolution module is designed to replaces the first two convolutional modules of the backbone network,aimed at enhancing the model's perception ability for specific shape objects and reducing its sensitivity to background noise.The algorithm was evaluated on the CCTSDB and TT100k datasets,and compared to YOLOv8s,the mAP50 values increased by 3.0%and 10.4%,respectively,demonstrating the effectiveness of the proposed method in improving the accuracy of traffic sign detection.
文摘Experimental therapies targeting immune and stromal cells,such as mast cells,cancer-associated fibroblasts,dendritic cells,and tumor endothelial cells,in the treatment of gastrointestinal solid tumors pose new and complex surgical and medico-legal challenges.These innovative treatments require that informed consent not be limited to simple acceptance of the medical procedure,but instead reflect a true relational and cognitive process grounded in understanding,free choice,and the ability to revoke consent at any time.In particular,it is essential that the patient understands the experimental nature of the therapy,its development stage,potential benefits and risks,as well as the implications for their health and personal dignity.In the case of stromal cell-based treatments,which may exert complex immunomodulatory effects or activate angiogenic pathways that are not yet fully understood,patients must be made fully aware that they are participating in a non-standardized therapy whose outcomes,whether beneficial or harmful,cannot yet be predicted with certainty.This requires particularly careful medical communication,using simple yet scientifically accurate explanations delivered in appropriate language,along with a final verification of the patient’s actual understanding.
基金funded by the National Natural Science Foundation of China (52061020).
文摘Quantitative analysis of aluminum-silicon(Al-Si)alloy microstructure is crucial for evaluating and controlling alloy performance.Conventional analysis methods rely on manual segmentation,which is inefficient and subjective,while fully supervised deep learning approaches require extensive and expensive pixel-level annotated data.Furthermore,existing semi-supervised methods still face challenges in handling the adhesion of adjacent primary silicon particles and effectively utilizing consistency in unlabeled data.To address these issues,this paper proposes a novel semi-supervised framework for Al-Si alloy microstructure image segmentation.First,we introduce a Rotational Uncertainty Correction Strategy(RUCS).This strategy employs multi-angle rotational perturbations andMonte Carlo sampling to assess prediction consistency,generating a pixel-wise confidence weight map.By integrating this map into the loss function,the model dynamically focuses on high-confidence regions,thereby improving generalization ability while reducing manual annotation pressure.Second,we design a Boundary EnhancementModule(BEM)to strengthen boundary feature extraction through erosion difference and multi-scale dilated convolutions.This module guides the model to focus on the boundary regions of adjacent particles,effectively resolving particle adhesion and improving segmentation accuracy.Systematic experiments were conducted on the Aluminum-Silicon Alloy Microstructure Dataset(ASAD).Results indicate that the proposed method performs exceptionally well with scarce labeled data.Specifically,using only 5%labeled data,our method improves the Jaccard index and Adjusted Rand Index(ARI)by 2.84 and 1.57 percentage points,respectively,and reduces the Variation of Information(VI)by 8.65 compared to stateof-the-art semi-supervised models,approaching the performance levels of 10%labeled data.These results demonstrate that the proposed method significantly enhances the accuracy and robustness of quantitative microstructure analysis while reducing annotation costs.
