长江经济带环境污染治理投资对生态效率的影响研究

环境污染治理投资是生态环境保护的资金来源，其投资规模和投资形式对生态效率产生着重大影响。本文构建生态效率测度指标和非期望的超效率SBM模型，测定了长江经济带9省2市的生态效率水平，再利用Tobit模型量化研究环境污染治理投资的总量及各投资形式对生态效率的影响程度，得出长江经济带环境污染治理投资对生态效率具有正向影响但影响程度一般，3种环境污染治理投资类型中的当年完成环保验收项目环保投资对生态效率影响程度最大且显著。     

Managing inter-firm projects: A systematic review and directions for future research

Although the management of inter-firm projects is increasingly being researched in a wide range of academic fields (project management, alliances and networks, organization studies), the findings of these studies rarely cross theoretical boundaries. In the present study, a systematic literature review of 219 contributions from 26 years of academic research on managing inter-firm projects identifies 22 key management issues underlying its contributions. Based on a two-dimensional framework (project stage and analytical sphere), a structured and integrative synthesis of relevant studies is outlined. Based on these findings, future investigations are proposed to focus on dynamic, contextual and structural aspects of the management of inter-firm projects.     

Development and application of a real-time water environment cyberinfrastructure for kayaker safety in the Apostle Islands,Lake Superior

Assessing all pertinent environmental variables to categorize a skill level to safely navigate the water environment can be difficult for inexperienced kayakers, especially at a remote site where internet access is limited. A real-time kayaker safety assessment of water environmental conditions at the Mainland Sea Caves of the Apostle Islands National Lakeshore, Lake Superior is achieved. We present a new cyberinfrastructure that provides kayakers with real-time data access and a Safety Index (SI) with consideration of multiple environmental factors to characterize the degree of navigational difficulty for classifying kayaker skill levels. Specifically, radar reflectivity is added to improve forecasts of dangerous conditions caused by convective storms using state-of-the-art weather and wave modeling. Spectral characteristics of surface waves are employed to correlate the occurrences of extreme and freak waves. In addition, unexpectedly dangerous conditions like coastal upwelling and freak wave occurrence due to changing wind directions are considered. A contingency plan is implemented to handle the issue of possibly missing required environmental data. Display of the SI and visualization of other real-time environmental data are communicated by a power-efficient kiosk. Web analytics demonstrates a public interest in real-time water conditions and the need for the on-site kiosk to provide the latest information before kayakers enter the water. The new real-time water environment cyberinfrastructure for kayaker safety in the Apostle Islands, Lake Superior has been successfully operated since 2014.     

Distributed ledger technology in supply chains: a transaction cost perspective

With the emergence of distributed ledger technology (DLT), numerous practitioners and researchers have proclaimed its beneficial impact on supply chain transactions in the future. However, the vast majority of DLT initiatives are discontinued after a short period. With the full potential of DLT laying far down the road, especially managers in supply chain management (SCM) seek for short-term cost-saving effects of DLT in order to achieve long-term benefits of DLT in the future. However, the extant research has bypassed grounding long-term as well as short-term effects of DLT on supply chain transaction with empirical data. We address this shortcoming, following an abductive research approach and combining empirical data from a multiple case study design with the corresponding literature. Our study reveals that the effects of DLT on supply chain transactions are two-sided. We found six effects of DLT solutions that have a cost-reducing or cost avoidance impact on supply chain transactions. In addition, we found two effects that change the power distribution between buyers and suppliers in transactions and a single effect that reduces the dependency of supply chain transactions on third parties. While cost-reducing and avoidance as well as dependency-reducing effects are positive effects, the change in power distribution might come with disadvantages. With these findings, the paper provides the first empirical evidence of the impact of DLT on supply chain transactions, which will enable managers to improve their assessment of DLT usage in supply chains.     

Distributionally robust optimization of home energy management system based on receding horizon optimization

This paper investigates the scheduling strategy of schedulable load in home energy management system (HEMS) under uncertain environment by proposing a distributionally robust optimization (DRO) method based on receding horizon optimization (RHO-DRO). First, the optimization model of HEMS, which contains uncertain variable outdoor temperature and hot water demand, is established and the scheduling problem is developed into a mixed integer linear programming (MILP) by using the DRO method based on the ambiguity sets of the probability distribution of uncertain variables. Combined with RHO, the MILP is solved in a rolling fashion using the latest update data related to uncertain variables. The simulation results demonstrate that the scheduling results are robust under uncertain environment while satisfying all operating constraints with little violation of user thermal comfort. Furthermore, compared with the robust optimization (RO) method, the RHO-DRO method proposed in this paper has a lower conservation and can save more electricity for users.     

A new ship energy management algorithm to the smart electricity grid system

In this paper, a new energy management algorithm has been suggested for the ships connected with alternative energies considering the smart electricity grid features. The algorithm focuses on the use of optimum energy source on the shipboard based on the priorities of authorities such as the most economic, environmental, or both criteria at the ports. The algorithm is performed in MATLAB, and several case studies are simulated to validate the results. The 5 maritime nations, which are at different regions: United States, Belgium, Turkey, China, and Australia, are taken into account in the case studies. The actual data of a bulk carrier ship have been used to achieve tangible results in the simulations. The results of the case studies are compared to determine the changes of energy cost and released emission to meet demand of electricity on the ships. Capital cost of the proposed concept is also given to make an economic evaluation. The results show that the ship energy management algorithm provides the significant economic and environmental advantages. This paper aims to contribute to the importance of the ships in the smart electricity grid concept for the maritime and electricity sector representatives.     

Blockchain in global supply chains and cross border trade: a critical synthesis of the state-of-the-art,challenges and opportunities

Blockchain possesses the potential of transforming global supply chain management. Gartner predicts that blockchain could be able to track $2?T of goods and services in their movement across the globe by 2023, and blockchain will be a more than $3 trillion business by 2030. Nowadays, a growing number of blockchain initiatives are disrupting traditional business models in each sector. In this paper, we provide a timely and holistic overview of the state-of-the-art, challenges, gaps and opportunities in global supply chain and trade operations for both the private sector and governmental agencies, by synthesising a wide range of resources from business leaders, global international organisations, leading supply chain consulting firms, research articles, trade magazines and conferences. We then identify collaborative schema and future research directions for industry, government, and academia to jointly work together in ensuring that the full potential of blockchain is unleashed amidst the socioeconomic, geopolitical and technological disruptions that global supply chains and trade are facing.     

Thermal-Disrupting Interface Mitigates Intercellular Cohesion Loss for Accurate Topical Antibacterial Therapy

Bacterial infections remain a leading threat to global health because of the misuse of antibiotics and the rise in drug-resistant pathogens. Although several strategies such as photothermal therapy and magneto-thermal therapy can suppress bacterial infections, excessive heat often damages host cells and lengthens the healing time. Here, a localized thermal managing strategy, thermal-disrupting interface induced mitigation (TRIM), is reported, to minimize intercellular cohesion loss for accurate antibacterial therapy. The TRIM dressing film is composed of alternative microscale arrangement of heat-responsive hydrogel regions and mechanical support regions, which enables the surface microtopography to have a significant effect on disrupting bacterial colonization upon infrared irradiation. The regulation of the interfacial contact to the attached skin confines the produced heat and minimizes the risk of skin damage during thermoablation. Quantitative mechanobiology studies demonstrate the TRIM dressing film with a critical dimension for surface features plays a critical role in maintaining intercellular cohesion of the epidermis during photothermal therapy. Finally, endowing wound dressing with the TRIM effect via in vivo studies in S. aureus infected mice demonstrates a promising strategy for mitigating the side effects of photothermal therapy against a wide spectrum of bacterial infections, promoting future biointerface design for antibacterial therapy.     

Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor

A semiconductor distributor that plays a third-party role in the supply chain will buy diverse components from different suppliers, warehouse and resell them to a number of electronics manufacturers with vendor-managed inventories, while suffering both risks of oversupply and shortage due to demand uncertainty. However, demand fluctuation and supply chain complexity are increasing due to shortening product life cycle in the consumer electronics era and long lead time for capacity expansion for high-tech manufacturing. Focusing realistic needs of a leading distributor for semiconductor components and modules, this study aims to construct a UNISON framework based on deep reinforcement learning (RL) for dynamically selecting the optimal demand forecast model for each of the products with the corresponding demand patterns to empower smart production for Industry 3.5. Deep RL that integrates deep learning architecture and RL algorithm can learn successful policies from the dynamic and complex real world. The reward function mechanism of deep RL can reduce negative impact of demand uncertainty. An empirical study was conducted for validation showing practical viability of the proposed approach. Indeed, the developed solution has been in real settings.     

基于二元水循环的水量-水质-水效联合调控模型开发与应用

为将我国最严格水资源管理制度的实践与二元水循环理论相结合，提高“三条红线”控制指标的科学性与合理性，本文以SWAT模型为基础，通过改进子流域划分方法、添加经济社会模块和人工用水模块，对其人工侧支循环模拟进行了系统的完善，开发了基于SWAT的水量-水质-水效联合调控模型SWAT_WAQER。以广西南流江流域为例，从国民经济用水量、河道径流与水质等方面对模型进行校验，并在此基础上划分了2030年“三条红线”控制指标。结果表明：该模型性能良好，能够用于不同节水情景下的国民经济用水量、污染物排放量、水功能区水质达标结果分析，可以作为科学制定“三条红线”控制指标的有力支撑工具。