BACKGROUND Return to work(RTW)serves as an indication for young and middle-aged colorectal cancer(CRC)survivors to resume their normal social lives.However,these survivors encounter significant challenges during their...BACKGROUND Return to work(RTW)serves as an indication for young and middle-aged colorectal cancer(CRC)survivors to resume their normal social lives.However,these survivors encounter significant challenges during their RTW process.Hence,scientific research is necessary to explore the barriers and facilitating factors of returning to work for young and middle-aged CRC survivors.AIM To examine the current RTW status among young and middle-aged CRC survivors and to analyze the impact of RTW self-efficacy(RTW-SE),fear of progression(FoP),eHealth literacy(eHL),family resilience(FR),and financial toxicity(FT)on their RTW outcomes.METHODS A cross-sectional investigation was adopted in this study.From September 2022 to February 2023,a total of 209 participants were recruited through a convenience sampling method from the gastrointestinal surgery department of a class A tertiary hospital in Chongqing.The investigation utilized a general information questionnaire alongside scales assessing RTW-SE,FoP,eHL,FR,and FT.To analyze the factors that influence RTW outcomes among young and middle-aged CRC survivors,Cox regression modeling and Kaplan-Meier survival analysis were used.RESULTS A total of 43.54%of the participants successfully returned to work,with an average RTW time of 100 days.Cox regression univariate analysis revealed that RTW-SE,FoP,eHL,FR,and FT were significantly different between the non-RTW and RTW groups(P<0.05).Furthermore,Cox regression multivariate analysis identified per capita family monthly income,job type,RTW-SE,and FR as independent influencing factors for RTW(P<0.05).CONCLUSION The RTW rate requires further improvement.Elevated levels of RTW-SE and FR were found to significantly increase RTW among young and middle-aged CRC survivors.Health professionals should focus on modifiable factors,such as RTW-SE and FR,to design targeted RTW support programs,thereby facilitating their timely reintegration into mainstream society.展开更多
The dynamic analysis of financial systems is a developing field that combines mathematics and economics to understand and explain fluctuations in financial markets.This paper introduces a new three-dimensional(3D)frac...The dynamic analysis of financial systems is a developing field that combines mathematics and economics to understand and explain fluctuations in financial markets.This paper introduces a new three-dimensional(3D)fractional financial map and we dissect its nonlinear dynamics system under commensurate and incommensurate orders.As such,we evaluate when the equilibrium points are stable or unstable at various fractional orders.We use many numerical methods,phase plots in 2D and 3D projections,bifurcation diagrams and the maximum Lyapunov exponent.These techniques reveal that financial maps exhibit chaotic attractor behavior.This study is grounded on the Caputo-like discrete operator,which is specifically influenced by the variance of the commensurate and incommensurate orders.Furthermore,we confirm the presence and measure the complexity of chaos in financial maps by the 0-1 test and the approximate entropy algorithm.Additionally,we offer nonlinear-type controllers to stabilize the fractional financial map.The numerical results of this study are obtained using MATLAB.展开更多
The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizat...The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.展开更多
In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading...In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.展开更多
Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep lear...Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.展开更多
With intensifying global climate change,humanity is confronted with unparalleled environmental challenges and risks.This study employs the staggered difference-in-difference model to examine the relationship between c...With intensifying global climate change,humanity is confronted with unparalleled environmental challenges and risks.This study employs the staggered difference-in-difference model to examine the relationship between climate policy and green innovation in the corporate financialization context.Using Chinese-listed company data from 2008 to 2020,our analysis reveals a favorable correlation between China’s carbon emission trading policy(CCTP)and advancements in green innovation.Furthermore,we find that the level of corporate financialization moderates this correlation,diminishing the driving effect of CCTP on green innovation.Additionally,results of heterogeneity analysis show that this moderating consequence is more evident in non-state owned and low-digitization enterprises compared with state-owned and high-digitization ones.Our findings contribute to the existing literature by clarifying the interaction between CCTP,green innovation,and corporate financialization.Our research provides valuable insights for policymakers and stakeholders seeking to strengthen climate policies and encourages green innovation in different types of businesses.展开更多
Objectives This paper aims to investigate the effects of enrollment in the Ethiopian community-based health insurance(CBHI)scheme on household preventive care activities and the timing of treatment-seeking behavior fo...Objectives This paper aims to investigate the effects of enrollment in the Ethiopian community-based health insurance(CBHI)scheme on household preventive care activities and the timing of treatment-seeking behavior for illness symptoms.There is growing concern about the financial sustainability of CBHI schemes in developing countries.However,few empirical studies have identified potential contributors,including ex-ante and ex-post moral hazards.Methods We implement a household fixed-effect panel data regression model,drawing on three rounds of household survey data collected face to face in districts where CBHI scheme is operational and in districts where it is not operational in Ethiopia.Results The findings show that enrolment in CBHI does not significantly influence household behaviour regarding preventive care activities such as water treatment before drinking and handwashing before meals.However,CBHI significantly increases delay in treatment-seeking behaviour for diseases symptoms.Particularly,on average,we estimate about 4-6 h delay for malaria symptoms,a little above 4 h for tetanus,and 10-11 h for tuberculosis among the insured households.Conclusions While there is evidence that CBHI improve the utilization of outpatient or primary care services,our study suggests that insured members may wait longer before visiting health facilities.This delay could be partly due to moral hazard problems,as insured households,particularly those from rural areas,may consider the opportunity costs associated with visiting health facilities for minor symptoms.Overall,it is essential to identify the primary causes of delays in seeking medical services and implement appropriate interventions to encourage insured individuals to seek early medical attention.展开更多
Sichuan Academy of Social Sciences is the think tank for the People’s Government of Sichuan Province and the Sichuan Provincial Committee of the CPC,with full financial backing of the Party and the government.The Aca...Sichuan Academy of Social Sciences is the think tank for the People’s Government of Sichuan Province and the Sichuan Provincial Committee of the CPC,with full financial backing of the Party and the government.The Academy consists of 16 institutes,1 graduate school,10 departments of scientific research management services.展开更多
Robotic total knee replacement(TKR)surgery has evolved over the years with the aim of improving the overall 80% satisfaction rate associated with TKR surgery.Proponents claim higher precision in executing the pre-oper...Robotic total knee replacement(TKR)surgery has evolved over the years with the aim of improving the overall 80% satisfaction rate associated with TKR surgery.Proponents claim higher precision in executing the pre-operative plan which results in improved alignment and possibly better clinical outcomes.Opponents suggest longer operative times with potentially higher complications and no superiority in clinical outcomes alongside increased costs.This editorial will summarize where we currently stand and the future implications of using robotics in knee replacement surgery.展开更多
As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into...As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into the classic Solow growth model,uncovering an inverted U-shaped relationship between them.A subsequent mechanism analysis explains the rationale behind this relationship.To empirically examine this relationship in China,the paper utilizes inter-provincial panel data from 2013 to 2021 and employs methodologies such as the two-way fixed effects and moderating effects models.These analyses have important implications for the sound and sustainable development of China’s financial industry.The findings indicate:(a)As China’s digital economy develops,its impact on financial regulatory costs follows an inverted U-shaped pattern,initially increasing and then declining.This conclusion remains valid after robustness tests.(b)The influence of the digital economy on regulatory costs depends on favorable external conditions.Specifically,the impact is more pronounced in regions and periods with better digital infrastructure and more abundant human capital.(c)Additionally,redundant resources moderate this impact,which can weaken the inverted U-shaped relationship.Our findings not only provide a theoretical foundation for understanding the impact of the digital economy on financial regulatory costs but also offer valuable policy insights for optimizing financial regulation in China.展开更多
In 2022,the United States stepped up its sanctions on Russia.Most notably,it restricted the flow of the Russian Central Bank's foreign exchange(forex)assets,using financial administrative power as a source of stra...In 2022,the United States stepped up its sanctions on Russia.Most notably,it restricted the flow of the Russian Central Bank's foreign exchange(forex)assets,using financial administrative power as a source of strategic leverage.This move should have reduced the appeal of US dollar assets but in reality has not accelerated as expected the decline of the greenback as a store of value.The US dollar's share of global forex reserves increased instead of decreased during 2022 and 2023.Despite the rise of economic costs caused by tightened US financial sanctions,countries that recognize the geopolitical role of the United States have further accepted the dollar's international status;their continued willingness to live with the dollar's“security premium”has given a fillip to the US dollar in the short term,boosting its appeal as a reserve currency.Meanwhile,de-dollarization of forex reserves has yet to reach a sufficient scale,thus falling short of significantly challenging the dollar's reign.From a longer-term perspective,as economic and security conditions shift,countries that accept the dollar's international role or seek de-dollarization may change their choices.As a result,four possible scenarios may arise:(i)the preeminence of the US dollar remains unthreatened;(ii)the international monetary system splits into blocs;(iii)the international monetary system fragments;and(iv)the dollar loses its throne.The author believes that the last scenario is the most likely outcome.展开更多
On September 27,the People's Bank of China (hereinafter referred to as the"central bank") announced that,from September 27,2024,the RRR (required reserve ratio)of financial institutions would be lowered ...On September 27,the People's Bank of China (hereinafter referred to as the"central bank") announced that,from September 27,2024,the RRR (required reserve ratio)of financial institutions would be lowered by 0.5 percentage points (excluding those that are subject to an RRR of 5%).The weighted average required reserve ratio for financial institutions is about 6.6% after this cut.At the same time,the central bank also announced that from September27,the interest rate for 7-day reverse repo operations in the open market will be adjusted from1.70%to 1.50%.展开更多
Non-communicable diseases (NCDs) are a significant global health challenge, contributing to 50% of worldwide morbidity and 63% of mortality. The burden is particularly substantial in low—and middle-income countries (...Non-communicable diseases (NCDs) are a significant global health challenge, contributing to 50% of worldwide morbidity and 63% of mortality. The burden is particularly substantial in low—and middle-income countries (LMICs), where 80% of NCD-related deaths occur. A quasi-experimental study addressed this challenge from May 2022 to March 2023. This study utilized a non-equivalent pre-and post-test design, with 300 participants in the quantitative and 70 in the qualitative. The study employed multistage cluster and random sampling to select ten community units, resulting in 150 community health volunteers (CHVs) in the control unit and 150 in the intervention group. Data collection was facilitated through the KOBO app. Qualitative data analysis involved six homogeneous focus group discussions (FGDs) and ten key informant interviews (KIIs), audio-recorded, transcribed, and analyzed using N-Vivo 12. Despite efforts to implement screening programs and improve linkages to care, significant barriers persist. This article reviews these barriers, drawing on current literature and empirical evidence. Key obstacles identified include limited awareness, inadequate healthcare infrastructure, cultural beliefs, financial constraints, fragmented healthcare systems, and challenges linking individuals to appropriate care services. The article explores strategies to overcome these barriers, emphasizing the importance of collaborative approaches involving stakeholders at various levels. Addressing these challenges aims to strengthen NCD screening and linkages to care, ultimately improving health outcomes for populations globally. Several recommendations emerge from the study’s findings and literature review. Raising awareness about NCDs and preventive measures is crucial and can be achieved through targeted health education campaigns and community outreach programs. Addressing healthcare infrastructure deficiencies, such as inadequate facilities and workforce shortages, is essential to ensure access to quality care. Cultural beliefs and practices also play a significant role in shaping health-seeking behavior. Engaging with local communities and incorporating cultural sensitivity into healthcare delivery can help bridge the gap between traditional beliefs and modern healthcare practices. Financial constraints pose a significant barrier to healthcare services, particularly in LMICs. Innovative financing mechanisms, such as health insurance schemes or subsidies, can help alleviate this burden and improve access to care. Furthermore, the fragmented nature of healthcare systems can hinder effective NCD management. Enhancing coordination and integration between primary care providers, specialists, and community health workers is essential to ensure seamless care delivery and patient follow-up. Finally, strengthening linkages between screening programs and care services is critical for the timely diagnosis and management of NCDs. This requires establishing robust referral systems and ensuring continuity of care for patients throughout their healthcare journey. In conclusion, addressing the multifaceted barriers to NCD screening and care linkage is essential for improving health outcomes globally. By implementing targeted interventions and fostering collaboration among stakeholders, progress can be made towards reducing the burden of NCDs and promoting population health.展开更多
In response to the recommendation by the American Assembly of Collegiate Schools of Business(AACSB,2002),which urged business schools to embark on interdisciplinary programs to facilitate boundary-spanning teaching an...In response to the recommendation by the American Assembly of Collegiate Schools of Business(AACSB,2002),which urged business schools to embark on interdisciplinary programs to facilitate boundary-spanning teaching and learning,many colleges have conducted one form of curriculum integration or the other.Many of these team-taught course integrations,however,concentrate on core business courses without reaching out to related courses in other disciplines.Moreover,due to some factors,the informational contents of management disclosures in annual reports and audit unqualified opinions may not align with the future viability of an enterprise.Using a“going concern concept”,this paper demonstrates how the addition of economics in business school curriculum integration could produce well-rounded business graduates.Economics concepts could unambiguously support the tests that cast doubts on firms’ability to continue operations.展开更多
Allianz Group recently released the Allianz Global Insurance Report,predicting that China will consolidate its position as the world’s second largest insurance market in the next decade.The report analyzes the busine...Allianz Group recently released the Allianz Global Insurance Report,predicting that China will consolidate its position as the world’s second largest insurance market in the next decade.The report analyzes the business performance of the global insurance market in 2023 and forecasts the development direction and trends of the global insurance industry in the next decade.2023:A year of significant growth According to the report,in 2023,the global insurance industry grew by an impressive 7.5%,which is the fastest rate since the pre-Global Financial Crisis(GFC)era.展开更多
On Apr.26th,2024,with the release of Marumi’s financial report,the listed enterprises of domestic cosmetics announced their performance for 2023.Upon analyzing the the list of TOP 10 listed enterprises of domestic co...On Apr.26th,2024,with the release of Marumi’s financial report,the listed enterprises of domestic cosmetics announced their performance for 2023.Upon analyzing the the list of TOP 10 listed enterprises of domestic cosmetics from 2021 to 2023(Only enterprises with makeups/daily cosmetics as their main businesses have been counted),it is found that there were new changes in the list for 2023.On the one hand,the TOP 1 listed enterprise of domestic cosmetics has been replaced by PROYA.展开更多
This paper proposes a blockchain-based system as a secure, efficient, and cost-effective alternative to SWIFT for cross-border remittances. The current SWIFT system faces challenges, including slow settlement times, h...This paper proposes a blockchain-based system as a secure, efficient, and cost-effective alternative to SWIFT for cross-border remittances. The current SWIFT system faces challenges, including slow settlement times, high transaction costs, and vulnerability to fraud. Leveraging blockchain technology’s decentralized, transparent, and immutable nature, the proposed system aims to address these limitations. Key features include modular architecture, implementation of microservices, and advanced cryptographic protocols. The system incorporates Proof of Stake consensus with BLS signatures, smart contract execution with dynamic pricing, and a decentralized oracle network for currency conversion. A sophisticated risk-based authentication system utilizes Bayesian networks and machine learning for enhanced security. Mathematical models are presented for critical components, including transaction validation, currency conversion, and regulatory compliance. Simulations demonstrate potential improvements in transaction speed and costs. However, challenges such as regulatory hurdles, user adoption, scalability, and integration with legacy systems must be addressed. The paper provides a comparative analysis between the proposed blockchain system and SWIFT, highlighting advantages in transaction speed, costs, and security. Mitigation strategies are proposed for key challenges. Recommendations are made for further research into scaling solutions, regulatory frameworks, and user-centric designs. The adoption of blockchain-based remittances could significantly impact the financial sector, potentially disrupting traditional models and promoting financial inclusion in underserved markets. However, successful implementation will require collaboration between blockchain innovators, financial institutions, and regulators to create an enabling environment for this transformative system.展开更多
The aim of this research project is to assess indirect water consumption,that represents the water consumed in the upstream part of the production life cycle.Estimations are provided for agriculture related companies,...The aim of this research project is to assess indirect water consumption,that represents the water consumed in the upstream part of the production life cycle.Estimations are provided for agriculture related companies,as agriculture represents 70%of water consumption on Earth.This consumption varies greatly according to the countries where supply chain is located.The estimation is attempted for 27 European listed companies in sectors relying on agriculture in its supply chain.A data is estimated for 22 companies,showing that indirect water consumption is much more important than direct one.Strategic questions raised through the estimation of indirect water consumption in various subsectors show the interest in this data,which represents the equivalent of Carbon Scope 3 for water issues.展开更多
THIRTY-FOUR years ago,the tallest building in Shanghai’s Pudong area was the Fire Watchtower on Dongchang Road.Its height was merely 24 meters.It was matched by Pudong’s GDP,which was a little over RMB six billion.T...THIRTY-FOUR years ago,the tallest building in Shanghai’s Pudong area was the Fire Watchtower on Dongchang Road.Its height was merely 24 meters.It was matched by Pudong’s GDP,which was a little over RMB six billion.Today,the tallest building in Pudong is the Shanghai Tower at a whopping height of 632 meters,and the skyline is full of majestic skyscrapers,such as the Oriental Pearl Tower and Shanghai World Financial Center.Proportionately,the district’s GDP has rocketed to over RMB 1.67 trillion.Reform and opening-up,started in 1978,has brought new vitality and prosperity,along with dramatic changes.展开更多
The study focuses on assessing the financial management practices and accounting mechanisms in agricultural cooperatives in Tulsipur Sub-Metropolitan,Dang District,Nepal with a focus on understanding their implication...The study focuses on assessing the financial management practices and accounting mechanisms in agricultural cooperatives in Tulsipur Sub-Metropolitan,Dang District,Nepal with a focus on understanding their implications for financial performance and organizational effectiveness.The sample size of total cooperatives(n=46)was divided into Savings and Credit Cooperatives(n=18)and Multipurpose Cooperatives(n=28),respectively,with a total number of respondents(n=138)categorized into managing directors,employees,and general members.Using a mixed-methods approach that combines quantitative analysis of financial data with qualitative insights gathered through interviews and surveys,the study emphasizes the importance of modern financial practices,improved reporting mechanisms,and relevant staff training for long-term sustainability.Recommendations include the integration of criteria and evaluation tools to assess cooperative performance,with Hamro Pahunch Multipurpose Cooperative identified as a high performer.Emphasizing the need for robust financial management strategies to navigate the complexity of the agricultural sector,manage risks,and achieve sustainable development,the study notes frequent preparation of financial management reports on a monthly and annual basis,and predominantly annual accounting management.Most cooperatives are using computerized models to present financial positions,but face challenges such as lack of marketing infrastructure,cooperative skills,and technical support.Ultimately,the study advocates for educating policy makers,cooperative leaders,practitioners and stakeholders on the role of effective financial management and accounting in enhancing the resilience,expansion and socio-economic impact of agricultural cooperatives,thereby fostering their long-term prosperity and viability as drivers of rural development and empowerment.展开更多
基金Supported by the Chongqing Medical University Program for Youth Innovation in Future Medicine,No.W0019Chongqing Municipal Education Commission’s 14th Five-Year Key Discipline Support Project,No.20240101 and No.20240102。
文摘BACKGROUND Return to work(RTW)serves as an indication for young and middle-aged colorectal cancer(CRC)survivors to resume their normal social lives.However,these survivors encounter significant challenges during their RTW process.Hence,scientific research is necessary to explore the barriers and facilitating factors of returning to work for young and middle-aged CRC survivors.AIM To examine the current RTW status among young and middle-aged CRC survivors and to analyze the impact of RTW self-efficacy(RTW-SE),fear of progression(FoP),eHealth literacy(eHL),family resilience(FR),and financial toxicity(FT)on their RTW outcomes.METHODS A cross-sectional investigation was adopted in this study.From September 2022 to February 2023,a total of 209 participants were recruited through a convenience sampling method from the gastrointestinal surgery department of a class A tertiary hospital in Chongqing.The investigation utilized a general information questionnaire alongside scales assessing RTW-SE,FoP,eHL,FR,and FT.To analyze the factors that influence RTW outcomes among young and middle-aged CRC survivors,Cox regression modeling and Kaplan-Meier survival analysis were used.RESULTS A total of 43.54%of the participants successfully returned to work,with an average RTW time of 100 days.Cox regression univariate analysis revealed that RTW-SE,FoP,eHL,FR,and FT were significantly different between the non-RTW and RTW groups(P<0.05).Furthermore,Cox regression multivariate analysis identified per capita family monthly income,job type,RTW-SE,and FR as independent influencing factors for RTW(P<0.05).CONCLUSION The RTW rate requires further improvement.Elevated levels of RTW-SE and FR were found to significantly increase RTW among young and middle-aged CRC survivors.Health professionals should focus on modifiable factors,such as RTW-SE and FR,to design targeted RTW support programs,thereby facilitating their timely reintegration into mainstream society.
文摘The dynamic analysis of financial systems is a developing field that combines mathematics and economics to understand and explain fluctuations in financial markets.This paper introduces a new three-dimensional(3D)fractional financial map and we dissect its nonlinear dynamics system under commensurate and incommensurate orders.As such,we evaluate when the equilibrium points are stable or unstable at various fractional orders.We use many numerical methods,phase plots in 2D and 3D projections,bifurcation diagrams and the maximum Lyapunov exponent.These techniques reveal that financial maps exhibit chaotic attractor behavior.This study is grounded on the Caputo-like discrete operator,which is specifically influenced by the variance of the commensurate and incommensurate orders.Furthermore,we confirm the presence and measure the complexity of chaos in financial maps by the 0-1 test and the approximate entropy algorithm.Additionally,we offer nonlinear-type controllers to stabilize the fractional financial map.The numerical results of this study are obtained using MATLAB.
文摘The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.
基金This project was funded by Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah underGrant No.(IFPIP-1127-611-1443)the authors,therefore,acknowledge with thanks DSR technical and financial support.
文摘In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.
基金funded by the Natural Science Foundation of Fujian Province,China (Grant No.2022J05291)Xiamen Scientific Research Funding for Overseas Chinese Scholars.
文摘Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.
基金support was obtained from the Fundamental Research Funds for the Central Universities[Grant No.JBK2307090].
文摘With intensifying global climate change,humanity is confronted with unparalleled environmental challenges and risks.This study employs the staggered difference-in-difference model to examine the relationship between climate policy and green innovation in the corporate financialization context.Using Chinese-listed company data from 2008 to 2020,our analysis reveals a favorable correlation between China’s carbon emission trading policy(CCTP)and advancements in green innovation.Furthermore,we find that the level of corporate financialization moderates this correlation,diminishing the driving effect of CCTP on green innovation.Additionally,results of heterogeneity analysis show that this moderating consequence is more evident in non-state owned and low-digitization enterprises compared with state-owned and high-digitization ones.Our findings contribute to the existing literature by clarifying the interaction between CCTP,green innovation,and corporate financialization.Our research provides valuable insights for policymakers and stakeholders seeking to strengthen climate policies and encourages green innovation in different types of businesses.
基金The authors acknowledge the financial support of the Dutch Research Council(NWO-WOTRO)(Grant No.W07.45.103.00)and the support of D.P.Hoijer Fonds,Erasmus Trustfonds,Erasmus University Rotterdam.
文摘Objectives This paper aims to investigate the effects of enrollment in the Ethiopian community-based health insurance(CBHI)scheme on household preventive care activities and the timing of treatment-seeking behavior for illness symptoms.There is growing concern about the financial sustainability of CBHI schemes in developing countries.However,few empirical studies have identified potential contributors,including ex-ante and ex-post moral hazards.Methods We implement a household fixed-effect panel data regression model,drawing on three rounds of household survey data collected face to face in districts where CBHI scheme is operational and in districts where it is not operational in Ethiopia.Results The findings show that enrolment in CBHI does not significantly influence household behaviour regarding preventive care activities such as water treatment before drinking and handwashing before meals.However,CBHI significantly increases delay in treatment-seeking behaviour for diseases symptoms.Particularly,on average,we estimate about 4-6 h delay for malaria symptoms,a little above 4 h for tetanus,and 10-11 h for tuberculosis among the insured households.Conclusions While there is evidence that CBHI improve the utilization of outpatient or primary care services,our study suggests that insured members may wait longer before visiting health facilities.This delay could be partly due to moral hazard problems,as insured households,particularly those from rural areas,may consider the opportunity costs associated with visiting health facilities for minor symptoms.Overall,it is essential to identify the primary causes of delays in seeking medical services and implement appropriate interventions to encourage insured individuals to seek early medical attention.
文摘Sichuan Academy of Social Sciences is the think tank for the People’s Government of Sichuan Province and the Sichuan Provincial Committee of the CPC,with full financial backing of the Party and the government.The Academy consists of 16 institutes,1 graduate school,10 departments of scientific research management services.
文摘Robotic total knee replacement(TKR)surgery has evolved over the years with the aim of improving the overall 80% satisfaction rate associated with TKR surgery.Proponents claim higher precision in executing the pre-operative plan which results in improved alignment and possibly better clinical outcomes.Opponents suggest longer operative times with potentially higher complications and no superiority in clinical outcomes alongside increased costs.This editorial will summarize where we currently stand and the future implications of using robotics in knee replacement surgery.
基金This study is funded by National Social Science Fund Major Project:“Research on Stimulating Innovation Vitality of Scientific and Technological Talent in the Context of Building a Talent Powerhouse”(21ZDA014)Research Start-Up Fund for Talent Recruitment of Sichuan Academy of Social Sciences:“Research on the Deep Integration of Sichuan’s Digital Economy and Real Economy to Support the Construction of a Modern Industrial System”(23RYJ03).
文摘As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into the classic Solow growth model,uncovering an inverted U-shaped relationship between them.A subsequent mechanism analysis explains the rationale behind this relationship.To empirically examine this relationship in China,the paper utilizes inter-provincial panel data from 2013 to 2021 and employs methodologies such as the two-way fixed effects and moderating effects models.These analyses have important implications for the sound and sustainable development of China’s financial industry.The findings indicate:(a)As China’s digital economy develops,its impact on financial regulatory costs follows an inverted U-shaped pattern,initially increasing and then declining.This conclusion remains valid after robustness tests.(b)The influence of the digital economy on regulatory costs depends on favorable external conditions.Specifically,the impact is more pronounced in regions and periods with better digital infrastructure and more abundant human capital.(c)Additionally,redundant resources moderate this impact,which can weaken the inverted U-shaped relationship.Our findings not only provide a theoretical foundation for understanding the impact of the digital economy on financial regulatory costs but also offer valuable policy insights for optimizing financial regulation in China.
文摘In 2022,the United States stepped up its sanctions on Russia.Most notably,it restricted the flow of the Russian Central Bank's foreign exchange(forex)assets,using financial administrative power as a source of strategic leverage.This move should have reduced the appeal of US dollar assets but in reality has not accelerated as expected the decline of the greenback as a store of value.The US dollar's share of global forex reserves increased instead of decreased during 2022 and 2023.Despite the rise of economic costs caused by tightened US financial sanctions,countries that recognize the geopolitical role of the United States have further accepted the dollar's international status;their continued willingness to live with the dollar's“security premium”has given a fillip to the US dollar in the short term,boosting its appeal as a reserve currency.Meanwhile,de-dollarization of forex reserves has yet to reach a sufficient scale,thus falling short of significantly challenging the dollar's reign.From a longer-term perspective,as economic and security conditions shift,countries that accept the dollar's international role or seek de-dollarization may change their choices.As a result,four possible scenarios may arise:(i)the preeminence of the US dollar remains unthreatened;(ii)the international monetary system splits into blocs;(iii)the international monetary system fragments;and(iv)the dollar loses its throne.The author believes that the last scenario is the most likely outcome.
文摘On September 27,the People's Bank of China (hereinafter referred to as the"central bank") announced that,from September 27,2024,the RRR (required reserve ratio)of financial institutions would be lowered by 0.5 percentage points (excluding those that are subject to an RRR of 5%).The weighted average required reserve ratio for financial institutions is about 6.6% after this cut.At the same time,the central bank also announced that from September27,the interest rate for 7-day reverse repo operations in the open market will be adjusted from1.70%to 1.50%.
文摘Non-communicable diseases (NCDs) are a significant global health challenge, contributing to 50% of worldwide morbidity and 63% of mortality. The burden is particularly substantial in low—and middle-income countries (LMICs), where 80% of NCD-related deaths occur. A quasi-experimental study addressed this challenge from May 2022 to March 2023. This study utilized a non-equivalent pre-and post-test design, with 300 participants in the quantitative and 70 in the qualitative. The study employed multistage cluster and random sampling to select ten community units, resulting in 150 community health volunteers (CHVs) in the control unit and 150 in the intervention group. Data collection was facilitated through the KOBO app. Qualitative data analysis involved six homogeneous focus group discussions (FGDs) and ten key informant interviews (KIIs), audio-recorded, transcribed, and analyzed using N-Vivo 12. Despite efforts to implement screening programs and improve linkages to care, significant barriers persist. This article reviews these barriers, drawing on current literature and empirical evidence. Key obstacles identified include limited awareness, inadequate healthcare infrastructure, cultural beliefs, financial constraints, fragmented healthcare systems, and challenges linking individuals to appropriate care services. The article explores strategies to overcome these barriers, emphasizing the importance of collaborative approaches involving stakeholders at various levels. Addressing these challenges aims to strengthen NCD screening and linkages to care, ultimately improving health outcomes for populations globally. Several recommendations emerge from the study’s findings and literature review. Raising awareness about NCDs and preventive measures is crucial and can be achieved through targeted health education campaigns and community outreach programs. Addressing healthcare infrastructure deficiencies, such as inadequate facilities and workforce shortages, is essential to ensure access to quality care. Cultural beliefs and practices also play a significant role in shaping health-seeking behavior. Engaging with local communities and incorporating cultural sensitivity into healthcare delivery can help bridge the gap between traditional beliefs and modern healthcare practices. Financial constraints pose a significant barrier to healthcare services, particularly in LMICs. Innovative financing mechanisms, such as health insurance schemes or subsidies, can help alleviate this burden and improve access to care. Furthermore, the fragmented nature of healthcare systems can hinder effective NCD management. Enhancing coordination and integration between primary care providers, specialists, and community health workers is essential to ensure seamless care delivery and patient follow-up. Finally, strengthening linkages between screening programs and care services is critical for the timely diagnosis and management of NCDs. This requires establishing robust referral systems and ensuring continuity of care for patients throughout their healthcare journey. In conclusion, addressing the multifaceted barriers to NCD screening and care linkage is essential for improving health outcomes globally. By implementing targeted interventions and fostering collaboration among stakeholders, progress can be made towards reducing the burden of NCDs and promoting population health.
文摘In response to the recommendation by the American Assembly of Collegiate Schools of Business(AACSB,2002),which urged business schools to embark on interdisciplinary programs to facilitate boundary-spanning teaching and learning,many colleges have conducted one form of curriculum integration or the other.Many of these team-taught course integrations,however,concentrate on core business courses without reaching out to related courses in other disciplines.Moreover,due to some factors,the informational contents of management disclosures in annual reports and audit unqualified opinions may not align with the future viability of an enterprise.Using a“going concern concept”,this paper demonstrates how the addition of economics in business school curriculum integration could produce well-rounded business graduates.Economics concepts could unambiguously support the tests that cast doubts on firms’ability to continue operations.
文摘Allianz Group recently released the Allianz Global Insurance Report,predicting that China will consolidate its position as the world’s second largest insurance market in the next decade.The report analyzes the business performance of the global insurance market in 2023 and forecasts the development direction and trends of the global insurance industry in the next decade.2023:A year of significant growth According to the report,in 2023,the global insurance industry grew by an impressive 7.5%,which is the fastest rate since the pre-Global Financial Crisis(GFC)era.
文摘On Apr.26th,2024,with the release of Marumi’s financial report,the listed enterprises of domestic cosmetics announced their performance for 2023.Upon analyzing the the list of TOP 10 listed enterprises of domestic cosmetics from 2021 to 2023(Only enterprises with makeups/daily cosmetics as their main businesses have been counted),it is found that there were new changes in the list for 2023.On the one hand,the TOP 1 listed enterprise of domestic cosmetics has been replaced by PROYA.
文摘This paper proposes a blockchain-based system as a secure, efficient, and cost-effective alternative to SWIFT for cross-border remittances. The current SWIFT system faces challenges, including slow settlement times, high transaction costs, and vulnerability to fraud. Leveraging blockchain technology’s decentralized, transparent, and immutable nature, the proposed system aims to address these limitations. Key features include modular architecture, implementation of microservices, and advanced cryptographic protocols. The system incorporates Proof of Stake consensus with BLS signatures, smart contract execution with dynamic pricing, and a decentralized oracle network for currency conversion. A sophisticated risk-based authentication system utilizes Bayesian networks and machine learning for enhanced security. Mathematical models are presented for critical components, including transaction validation, currency conversion, and regulatory compliance. Simulations demonstrate potential improvements in transaction speed and costs. However, challenges such as regulatory hurdles, user adoption, scalability, and integration with legacy systems must be addressed. The paper provides a comparative analysis between the proposed blockchain system and SWIFT, highlighting advantages in transaction speed, costs, and security. Mitigation strategies are proposed for key challenges. Recommendations are made for further research into scaling solutions, regulatory frameworks, and user-centric designs. The adoption of blockchain-based remittances could significantly impact the financial sector, potentially disrupting traditional models and promoting financial inclusion in underserved markets. However, successful implementation will require collaboration between blockchain innovators, financial institutions, and regulators to create an enabling environment for this transformative system.
文摘The aim of this research project is to assess indirect water consumption,that represents the water consumed in the upstream part of the production life cycle.Estimations are provided for agriculture related companies,as agriculture represents 70%of water consumption on Earth.This consumption varies greatly according to the countries where supply chain is located.The estimation is attempted for 27 European listed companies in sectors relying on agriculture in its supply chain.A data is estimated for 22 companies,showing that indirect water consumption is much more important than direct one.Strategic questions raised through the estimation of indirect water consumption in various subsectors show the interest in this data,which represents the equivalent of Carbon Scope 3 for water issues.
文摘THIRTY-FOUR years ago,the tallest building in Shanghai’s Pudong area was the Fire Watchtower on Dongchang Road.Its height was merely 24 meters.It was matched by Pudong’s GDP,which was a little over RMB six billion.Today,the tallest building in Pudong is the Shanghai Tower at a whopping height of 632 meters,and the skyline is full of majestic skyscrapers,such as the Oriental Pearl Tower and Shanghai World Financial Center.Proportionately,the district’s GDP has rocketed to over RMB 1.67 trillion.Reform and opening-up,started in 1978,has brought new vitality and prosperity,along with dramatic changes.
文摘The study focuses on assessing the financial management practices and accounting mechanisms in agricultural cooperatives in Tulsipur Sub-Metropolitan,Dang District,Nepal with a focus on understanding their implications for financial performance and organizational effectiveness.The sample size of total cooperatives(n=46)was divided into Savings and Credit Cooperatives(n=18)and Multipurpose Cooperatives(n=28),respectively,with a total number of respondents(n=138)categorized into managing directors,employees,and general members.Using a mixed-methods approach that combines quantitative analysis of financial data with qualitative insights gathered through interviews and surveys,the study emphasizes the importance of modern financial practices,improved reporting mechanisms,and relevant staff training for long-term sustainability.Recommendations include the integration of criteria and evaluation tools to assess cooperative performance,with Hamro Pahunch Multipurpose Cooperative identified as a high performer.Emphasizing the need for robust financial management strategies to navigate the complexity of the agricultural sector,manage risks,and achieve sustainable development,the study notes frequent preparation of financial management reports on a monthly and annual basis,and predominantly annual accounting management.Most cooperatives are using computerized models to present financial positions,but face challenges such as lack of marketing infrastructure,cooperative skills,and technical support.Ultimately,the study advocates for educating policy makers,cooperative leaders,practitioners and stakeholders on the role of effective financial management and accounting in enhancing the resilience,expansion and socio-economic impact of agricultural cooperatives,thereby fostering their long-term prosperity and viability as drivers of rural development and empowerment.