Impact of Prevailing Wages on the Cost among the Various Construction Trades

In 1997, the Ohio Senate passed Senate Bill 102 which established the Ohio School Facilities Commission as a separate agency to oversee the rebuilding projects of the public schools in Ohio. The bill also exempted the construction contractors from paying prevailing wages on these projects on the hypothesis that this exemption would lower the construction cost. The purpose of this study is to investigate this hypothesis through the statistical analysis of 8,093 bids received from the years 2000 through 2007 for the schools＇ construction. Union contractors who paid their workers union wages and non-union contractors who did not pay prevailing wages bid these projects. The hypothesis, that prevailing wage laws increased the construction cost, was tested by comparing the bids/SF （square foot） from both groups （union and nonunion） for the different construction trades. The study indicated that there was statistical significant difference between the bids/square foot for union contractors and the bids/square foot for non-union contractors for only the following trades： earthwork, existing conditions, plumbing, electrical and HVAC （heating, ventilation and air conditioning）. The averages of bids/SF from the union contractors were higher than those from the non-union contractors for earthwork, existing conditions and plumbing works, and the opposite for electrical and HVAC works. There was no statistical significant difference in the bids from the communications, concrete, conveying equipment, electronic safety and security, equipment, finishes, fire suppression, furnishings, masonry, openings, structural steel, thermal and moisture protection, plastics and composites and wood works.

China Should Stimulate Bilateral Good Trades to Cope with the Challenge between China and Germany

2017 marks the 45th anniversary of diplomatic relations between China and Germany. Now ＇Germany is the fifth largest tradepartner of China around the world, and the largest one in Europe, while China has topped the United States and France and become the largest trade partner of Germany.

Being a Jack of All Trades or Good at One Thing

The Double Take column looks at a single topic from an African and Chinese perspective. This month we discuss the pros and cons of being a generalist or specialist.I was born in Yangzhou, Jiangsu Province, in 1956, and when I started working in the 1970s,being a jack of all trades was not an option.

Variation of Chlorophyll Fluorescence in Leaf Color Mutant of Wandering Jew(Tradescantia fuminensis)Induced by Heavy Ions Irradiation

The thermo-sensitive leaf color mutant of Wandering jew(Tradescantiafiumiensis)was obtained by heavy ion irradiation at HIRFL.The young leaves of this mutant are pink under low-temperature conditions,and the turn back to green under high-temperature conditions.

Blockchain-Enabled Privacy Protection and Access Control Scheme Towards Sensitive Digital Assets Management

With the growth of requirements for data sharing,a novel business model of digital assets trading has emerged that allows data owners to sell their data for monetary gain.In the distributed ledger of blockchain,however,the privacy of stakeholder's identity and the confidentiality of data content are threatened.Therefore,we proposed a blockchainenabled privacy-preserving and access control scheme to address the above problems.First,the multi-channel mechanism is introduced to provide the privacy protection of distributed ledger inside the channel and achieve coarse-grained access control to digital assets.Then,we use multi-authority attribute-based encryption(MAABE)algorithm to build a fine-grained access control model for data trading in a single channel and describe its instantiation in detail.Security analysis shows that the scheme has IND-CPA secure and can provide privacy protection and collusion resistance.Compared with other schemes,our solution has better performance in privacy protection and access control.The evaluation results demonstrate its effectiveness and practicability.

Temporal and spatial evolution of global major grain trade patterns

The complex and volatile international landscape has significantly impacted global grain supply security. This study uses a complex network analysis model to examine the evolution and trends of the global major grain trade from 1990 to 2020, focusing on network topology, centrality ranking, and community structure. There are three major findings. First, the global major grain trade network has expanded in scale, with a growing emphasis on diversification and balance. During the study period, the United States, Canada, China, and Brazil were the core nodes of the network. Grain-exporting countries were mainly situated in Asia, the Americas, and Europe, and importing countries in Asia, Africa, and Europe. Second, a significant increase in the number of high centrality countries with high export capacity occurred, benefiting from natural advantages such as fertile land and favorable climates. Third, the main global grain trade network is divided into four communities, with the Americas-Europe community being the largest and most widespread. The formation of the community pattern was influenced by geographic proximity, driven by the core exporting countries. Therefore, the world needs to enhance the existing trade model, promote the multi-polarization of the grain trade network, and establish a global vision for the future community. Countries and regions should participate actively in global grain trade security governance and institutional reform, expand trade links with other countries, and optimize import and export policies to reduce trade risks.

Electricity Carbon Quota Trading Scheme based on Certificateless Signature and Blockchain

The carbon tradingmarket can promote“carbon peaking”and“carbon neutrality”at low cost,but carbon emission quotas face attacks such as data forgery,tampering,counterfeiting,and replay in the electricity trading market.Certificateless signatures are a new cryptographic technology that can address traditional cryptography’s general essential certificate requirements and avoid the problem of crucial escrowbased on identity cryptography.However,most certificateless signatures still suffer fromvarious security flaws.We present a secure and efficient certificateless signing scheme by examining the security of existing certificateless signature schemes.To ensure the integrity and verifiability of electricity carbon quota trading,we propose an electricity carbon quota trading scheme based on a certificateless signature and blockchain.Our scheme utilizes certificateless signatures to ensure the validity and nonrepudiation of transactions and adopts blockchain technology to achieve immutability and traceability in electricity carbon quota transactions.In addition,validating electricity carbon quota transactions does not require time-consuming bilinear pairing operations.The results of the analysis indicate that our scheme meets existential unforgeability under adaptive selective message attacks,offers conditional identity privacy protection,resists replay attacks,and demonstrates high computing and communication performance.

Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital Financial Frontier and Enterprise Information Systems

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.

Specialization or Diversification:Which is More Conducive to Foreign Trade Resilience?Evidence from China-Russia Border Regions in Northeast China

Under the background of complex international situation,how to build the special geo-economic space of China-Russia bor-der lies in strengthening their foreign trade resilience against external shocks.Based on empirical evidence from ten prefecture-level China-Russia border regions in Northeast China,this paper analyzed the spatiotemporal evolution of foreign trade resilience under different shocks.Furthermore,through the Panel Regression model,the mechanism of the industrial structure on the foreign trade resilience in contraction period and expansion period was discussed.The results showed that:1)from 2004 to 2021,foreign trade in China-Russia border regions experienced five phases.The overall foreign trade resilience was higher than expected,showing a rising volatility trend,but there was significant spatial heterogeneity in the ability of cities to cope with shocks.2)Highly specialized clusters were mainly concentrated in Yichun,Heihe and Da Hinggan Ling Prefecture,while Mudanjiang and Yanbian performed better in related and unrelated diversification.3)In different stages of economic system evolution,the response mode,degree and result of border foreign trade resilience to regional industrial structure showed obvious stage characteristics.During the contraction period,related diversification was more conducive to improving the resistance through risk spillovers.During the expansion period,specialization played a more significant role in improving regional resilience through self-reinforcing effect.These results are beneficial for expanding the resilience theory,ensuring border economic security and optimizing border industrial investment layout.

An Energy Trading Method Based on Alliance Blockchain and Multi-Signature

Blockchain,known for its secure encrypted ledger,has garnered attention in financial and data transfer realms,including the field of energy trading.However,the decentralized nature and identity anonymity of user nodes raise uncertainties in energy transactions.The broadcast consensus authentication slows transaction speeds,and frequent single-point transactions in multi-node settings pose key exposure risks without protective measures during user signing.To address these,an alliance blockchain scheme is proposed,reducing the resource-intensive identity verification among nodes.It integrates multi-signature functionality to fortify user resources and transac-tion security.A novel multi-signature process within this framework involves neutral nodes established through central nodes.These neutral nodes participate in multi-signature’s signing and verification,ensuring user identity and transaction content privacy.Reducing interactions among user nodes enhances transaction efficiency by minimizing communication overhead during verification and consensus stages.Rigorous assessments on reliability and operational speed highlight superior security performance,resilient against conventional attack vectors.Simulation shows that compared to traditional solutions,this scheme has advantages in terms of running speed.In conclusion,the alliance blockchain framework introduces a novel approach to tackle blockchain’s limitations in energy transactions.The integrated multi-signature process,involving neutral nodes,significantly enhances security and privacy.The scheme’s efficiency,validated through analytical assessments and simulations,indicates robustness against security threats and improved transactional speeds.This research underscores the potential for improved security and efficiency in blockchain-enabled energy trading systems.

A coordinated operation method of wind-PV-hydrogenstorage multi-agent energy system

Wind-photovoltaic(PV)-hydrogen-storage multi-agent energy systems are expected to play an important role in promoting renewable power utilization and decarbonization.In this study,a coordinated operation method was proposed for a wind-PVhydrogen-storage multi-agent energy system.First,a coordinated operation model was formulated for each agent considering peer-to-peer power trading.Second,a coordinated operation interactive framework for a multi-agent energy system was proposed based on the theory of the alternating direction method of multipliers.Third,a distributed interactive algorithm was proposed to protect the privacy of each agent and solve coordinated operation strategies.Finally,the effectiveness of the proposed coordinated operation method was tested on multi-agent energy systems with different structures,and the operational revenues of the wind power,PV,hydrogen,and energy storage agents of the proposed coordinated operation model were improved by approximately 59.19%,233.28%,16.75%,and 145.56%,respectively,compared with the independent operation model.

Production and trade trend of oils and oilseeds in BRICS countries

In order to promote agricultural production and trade cooperation among BRICS countries,and ensure the security and stability of the oils and oilseeds industrial and supply chains in China and the world,the production,consumption,trade trend,and cooperation potential of oils and oilseeds in BRICS countries were expounded,and relevant policy recommendations were put forward.Most of the BRICS countries are major agricultural producers,and they are also important agricultural product consumption markets in the world.In 2023/2024,the production and consumption of oilseeds in BRICS countries account for nearly half of the world's total;the production of vegetable oils exceeds a quarter of the world's total,and the consumption of vegetable oils accounts for 40%of the world's total.In 2023/2024,the import and export volume of oilseeds exceeds half of the world's total;vegetable oil imports account for 40%of the world's total,and exports account for about one tenth of the world's total.China's imports of oilseeds and oils from BRICS countries account for 68%and 29%of its global imports in 2023,respectively.BRICS countries are rich in agricultural land resources,have great potential for oils and oilseeds production,obvious complementary advantages in trade structure,and huge space for future cooperation.It is suggested that Brazil should be included in the"Belt and Road"co-construction category to promote the continuous deepening of agricultural cooperation between China and Brazil.It is suggested to explore regional agricultural trade agreements among BRICS countries,promote currency settlement and exchange among BRICS countries,and enhance the facilitation and stability of BRICS trade.It is suggested that China should increase its investment in BRICS countries and export advanced technology and management experience to benefit local agricultural development and achieve a mutually beneficial and win-win situation.

Impact of correlated private signals on continuous-time insider trading

A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establish three lemmas:normal corre-lation,equivalent pricing and equivalent profit,which can guarantee to turn our model into a model with insider knowing full information.Then we investigate the impact of the two correlated signals on the market equilibrium consisting of optimal insider trading strategy and semi-strong pricing rule.It shows that in the equilibrium,(1)the market depth is constant over time;(2)if the two noisy signals are not linerly correlated,then all private information of the insider is incorporated into prices in the end while the whole information on the asset value can not incorporated into prices in the end;(3)if the two noisy signals are linear correlated such that the insider can infer the whole information of the asset value,then our model turns into a model with insider knowing full information;(4)if the two noisy signals are the same then the total ex ant profit of the insider is increasing with the noise decreasing,while down to O as the noise going up to infinity;(5)if the two noisy signals are not linear correlated then with one noisy signal fixed,the total ex ante profit of the insider is single-peaked with a unique minimum with respect to the other noisy signal value,and furthermore as the noisy value going to O it gets its maximum,the profit in the case that the real value is observed.

Spatial Heterogeneity of Embedded Water Consumption from the Perspective of Virtual Water Surplus and Deficit in the Yellow River Basin,China

Virtual water trade(VWT)provides a new perspective for alleviating water crisis and has thus attracted widespread attention.However,the heterogeneity of virtual water trade inside and outside the river basin and its influencing factors remains further study.In this study,for better investigating the pattern and heterogeneity of virtual water trade inside and outside provincial regions along the Yellow River Basin in 2015 using the input-output model(MRIO),we proposed two new concepts,i.e.,virtual water surplus and virtual water deficit,and then used the Logarithmic Mean Divisia Index(LMDI)model to identify the inherent mechanism of the imbalance of virtual water trade between provincial regions along the Yellow River Basin and the other four regions in China.The results show that:1)in provincial regions along the Yellow River Basin,the less developed the economy was,the larger the contribution of the agricultural sector in virtual water trade,while the smaller the contribution of the industrial sector.2)Due to the large output of agricultural products,the upstream and midstream provincial regions of the Yellow River Basin had a virtual water surplus,with a net outflow of virtual water of 2.7×10^(8) m^(3) and 0.9×10^(8) m^(3),respectively.3)provincial regions along the Yellow River Basin were in a virtual water deficit with the rest of China,and the decisive factor was the active degree of trade with the outside.This study would be beneficial to illuminate the trade-related water use issues in provincial regions along the Yellow River Basin,which has farreaching practical signific-ance for alleviating water scarcity.

Moderating effect of corporate financialization on the impact of climate policy on corporate green innovation:Evidence from China

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.

“China Shock”or China Dividend?-China GVC Participation’s Effects on Trading Partners’Technological Progress

This paper explores the effects of China’s global value chain(GVC)participation on technological progress in trading-partner countries based on estimated data on value-added trade between China and 52 trading partners.We find that,first,although China’s exports lowered the total factor productivity(TFP)of its trading partners(competitive effect),its imports greatly increased trading partners’TFP(effect of scale).This implies that China’s GVC participation is beneficial to its trading partners’technological progress in the form of a considerable technology dividend effect.Second,China’s export dividend effect compensates for the negative effect of Chinese competition on trading partners’technological progress;the innovation effects attributable to China’s imports reinforce the positive effects of scale on technological progress.When innovation is factored in,the China dividend thus becomes further reinforced.Third,China’s merchandise imports have a diminishing positive effect on technological progress in trading partners as geographical distance increases,but trade in services transcends geographical boundaries,and the positive technological progress effect of China’s service imports do not diminish as distance increases.We find that the“China dividend”from China’s GVC participation is a significant contributor to technological progress in partner nations,and China’s imports are conducive to innovation and technological progress in developed countries in the long run.

Distributed Robust Scheduling Optimization ofWind-Thermal-Storage System Based on Hybrid Carbon Trading andWasserstein Fuzzy Set

A robust scheduling optimization method for wind–fire storage system distribution based on the mixed carbon trading mechanism is proposed to improve the rationality of carbon emission quota allocation while reducing the instability of large-scale wind power access systems.A hybrid carbon trading mechanism that combines shortterm and long-term carbon trading is constructed,and a fuzzy set based onWasserstein measurement is proposed to address the uncertainty of wind power access.Moreover,a robust scheduling optimization method for wind–fire storage systems is formed.Results of the multi scenario comparative analysis of practical cases show that the proposed method can deal with the uncertainty of large-scale wind power access and can effectively reduce operating costs and carbon emissions.