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To achieve California’s ambitious climate goals, a shift to hydrogen fuel for some transportation sectors may be essential.In this report, we explore the build-out of a hydrogen fuel distribution system including uptake of light-, medium-, and heavy-duty fuel cell electric vehicles. Our analysis of Base and High Case scenarios includes costs of building and operating a hydrogen vehicle and fuel system and estimates workforce impacts. We consider scenarios with about 125,000 vehicles by 2030 in the Base Case and 250,000 in the high case. This increases by an order of magnitude to 2045. Vehicle and station investment costs associated with the Base Case reach anywhere from $4 to 12 billion USD by 2030 and increase by a factor of eight by 2045. Costs per kg of hydrogen, including fuel transmission to stations and station costs delivered to vehicles, could be in the range of $4 to 8 per kg. This becomes $6 to 10/kg as a final delivered cost, if production of hydrogen were to cost $2/kg. Workforce impacts in the Base Case include 600 to 2,200 jobs created by 2030, rising rapidly thereafter. This report was prepared by the ITS-UC Davis Energy Futures Hydrogen Program in partnership with the UCLA Luskin Center for Innovation.

Efficient traffic safety management necessitates real‐time crash risk prediction using expressway characteristics. With the emergence of autonomous vehicles (AVs), the development and evaluation of variable speed limit (VSL) strategies, a key active traffic management technique, become crucial for enhancing safety and mobility in mixed traffic flows. This underscores the need for optimized VSL strategies to accommodate both conventional and AVs. This paper presents a study on the development of VSL control algorithms using deep reinforcement learning in a microscopic traffic simulation. As the rewards function, time‐to‐collision and speed were considered. To enhance traffic safety, VSL strategies were refined across various market penetration of connected AVs. Analysis revealed that safety and traffic density are improved by 53% and 59%, respectively, in market penetration rate (MPR) 50, marking significant safety improvements in congested and low MPR scenarios. These findings present the importance of developing and evaluating VSL strategies for mixed traffic flow, particularly in the context of increasing the prevalence of connected and AVs. [ABSTRACT FROM AUTHOR]

This study introduces a framework to maximize societal benefits associated with the autonomous vehicle (AV)‐dedicated lane implementation at large‐scale transportation networks, considering the travel time savings and the required investments to prepare the infrastructure for their deployment. To this end, a bi‐level optimization problem is formulated. The upper level determines the links for dedicated lane deployment, while at the lower level, a mesoscopic traffic simulation tool is employed to enable a realistic representation of these vehicles in a mixed traffic. The problem is solved using the genetic algorithm. To further reduce the computational burden, this study adopts a clustering method based on the snake algorithm to group the candidate links and reduce the size of the solution space. The proposed framework is successfully applied to the case study of Chicago downtown network, considering various demand levels, AV market penetration rates, and implementation approaches. The results highlight the need for optimizing the placement of AV‐dedicated lanes (AVDLs) to ensure the economically beneficial adoption of this strategy across different scenarios. This study provides transportation planners with key operational insights to facilitate the effective adoption of AVDLs during the transitional phase from human‐driven vehicles to a fully AV environment. [ABSTRACT FROM AUTHOR]

Solid Oxide Fuel Cells (SOFCs) are capable of generating electrical and thermal power with very high conversion efficiency and almost no pollutant emissions into the atmosphere. Despite extensive literature on SOFC-based energy system models and experimental testing at the cell and short-stack level, there is currently a lack of performance data for SOFC modules under actual field conditions. To fill this gap, the present work investigates the energy and environmental performance of six SOFC modules, ranging in size from 10 to 60 kW, over thousands of hours of operation. These systems, supplied by the three leading SOFC manufacturers in Europe, have been installed and operated in different non-residential buildings worldwide, as part of the European Comsos project. The aim of this study is to establish a comprehensive set of field operation data to characterise commercial-scale SOFC systems. Specifically, raw data are processed to derived electrical and thermal efficiency maps, degradation rates and pollutant emissions, including particulate matter (PM), nitrogen oxides (NO x) and carbon monoxide (CO). A comparison with competing technologies is also provided to better highlight the potential benefits of adopting SOFC-based cogeneration systems. Values in the range of 51–61% were found for the system-level electrical efficiency under rated conditions. The electrical efficiency also remained consistently high across a wide modulation range (between 50% and 100% of rated power), with peak values reaching 65%. In addition, promising results were obtained for the average percentage loss in electrical efficiency, with a minimum value of 0.7%/1000 h. Regarding the environmental analysis, NO x and CO emissions were analysed at both constant and variable power output, proving to be impressively low across the entire modulation range. The same applies to PM concentrations, which were below ambient level. Overall, SOFCs demonstrated to be one of the best cogeneration solutions for commercial-scale systems (tens to hundreds of kW in size), from both an energy and environmental perspective. However, further reductions in costs and dedicated financial schemes are necessary for a widespread market penetration. [Display omitted] • Energy and environmental performance from the field operation of six SOFC systems. • Rated AC electrical efficiency of 51%–61%, with stable performance at partial load. • Maximum AC electrical efficiency of up to 65%. • Percentage loss in AC electrical efficiency of 0.7 %/1000 h. • Very low values for NO x and CO emissions, even at partial load. [ABSTRACT FROM AUTHOR]

Fighting climate change has become a major task worldwide. One of the key energy sectors to emit greenhouse gases is transportation. Therefore, long term strategies all over the world have been set up to reduce on-road combustion emissions. In this context, the road freight sector faces significant challenges in decarbonization, driven by its limited availability of low-emission fuels and commercialized zero-emission vehicles compared with its high energy demand. In this work, we develop the Mobility and Energy Transportation Analysis (META) Model, a python-based optimization model to quantify the impact of transportation projected policies on freight transport by projecting conventional and alternative fuel technologies market acceptance as well as greenhouse gas (GHG) emissions. Along with introducing e-fuels as an alternative refueling option for conventional vehicles, META investigates the market opportunities of Mobile Carbon Capture (MCC) until 2050. To accurately assess this technology, a techno-economic analysis is essential to compare MCC abatement cost to alternative decarbonization technologies such as electric trucks. The novelty of this work comes from the detailed cost categories taken into consideration in the analysis, including intangible costs associated with heavy-duty technologies, such as recharging/refueling time, cargo capacity limitations, and consumer acceptance towards emerging technologies across different regions. Based on the study results, the competitive total cost of ownership (TCO) and marginal abatement cost (MAC) values of MCC make it an economically promising alternative option to decarbonize the freight transport sector. Both in the KSA and EU, MCC options could reach greater than 50% market shares of all ICE vehicle sales, equivalent to a combined 35% of all new sales shares by 2035. [ABSTRACT FROM AUTHOR]

Some firms in the technology sector choose to cooperate with competitors ("co-opetition") in standard setting organizations (SSOs). These SSOs create technology standards that facilitate rapid market penetration of new technologies such as Wi-Fi, Bluetooth, and 4G. Active participation in the standard setting process requires the exchange of proprietary information with competitors. Although the goal of such information sharing is to further a technology or a product market, firms potentially receive an additional benefit from access to competitor and industry information. We examine whether contributing to SSO committees enhances a firm's information set and allows managers to better predict future sales. We find that the centrality of a firm's location within the network of SSO collaborators is positively related to the accuracy of the firm's sales forecasts. This relation is stronger when firms exchange more information with direct competitors and with larger firms, when forecasting is more difficult ex ante, and when firms forecast over longer horizons. Our findings show that collaborating with competitors in the product market provides an important additional benefit of improving the manager's information set. This paper was accepted by David Simchi-Levi, accounting. Funding: This work was supported by the Wharton School, Institut Européen d'Administration des Affaires, the Institut Européen d'Administration des Affaires-Wharton Alliance, and the Mack Institute for Innovation Management. Supplemental Material: The data and online appendix are available at https://doi.org/10.1287/mnsc.2021.03152. [ABSTRACT FROM AUTHOR]

Car-sharing is a travel mode that can serve as an alternative to private cars, helping to reduce urban pollution. However, currently, there is a low willingness among travelers to use car-sharing, which is reflected in both low market penetration and user frequency. Therefore, it is essential for the government to encourage the use of car-sharing by providing subsidies. To better encourage the usage of car-sharing, this paper applies a two-fold evolutionary game model involving travelers and the government to explore the impact of subsidies on travelers' choices, and the factors that could affect the subsidies' efficiency. A simulation, using data from Beijing, was conducted to determine the implications of subsidy policies. The results show that a mileage-based subsidy and a fixed subsidy are applicable to travel of high and low mileages respectively, and under both subsidy modes, subsidies for trips with short duration or short pick-up and return time are more effective. Furthermore, we find that the efficiency of subsidies increases as the scale of car-sharing users, demand elasticity, or total number of travelers increases. Additionally, the subsidy levels should be lower than the environmental benefits of car-sharing but higher than the difference in travel costs between private cars and car-sharing. Future work will involve other game players such as car-sharing operators in order to draw deeper conclusions, and will involve the collection of data from more countries and cities to develop the robustness of the conclusions. [ABSTRACT FROM AUTHOR]

Vaccine manufacturing fosters the prevention, control, and eradication of infectious diseases. Recombinant DNA and in vitro (IVT) mRNA vaccine manufacturing technologies were enforced to combat the recent pandemic. Despite the impact of these technologies, there exists no scientific announcement that compares them. Digital Shadows are employed in this study to simulate each technology, investigating root cause deviations, technical merits, and liabilities, evaluating cost scenarios. Under this lens we provide an unbiased, advanced comparative technoeconomic study, one that determines which of these manufacturing platforms are suited for the two types of vaccines considered (monoclonal antibodies or antigens). We find recombinant DNA technology to exhibit higher Profitability Index due to lower capital and starting material requirements, pertaining to lower Minimum Selling Price per Dose values, delivering products of established quality. However, the potency of the mRNA, the streamlined and scalable synthetic processes involved and the raw material availability, facilitate faster market penetration and product flexibility, constituting these vaccines preferable whenever short product development cycles become a necessity. [ABSTRACT FROM AUTHOR]

Due to the rapid evolution of autonomous driving technology and the complexity of market penetration mechanisms, establishing a reliable quantitative research approach for measuring autonomous vehicle (AV) penetration and effectively validating forecasted outcomes poses significant challenges. To address this issue, this paper overcomes data limitations by starting from the perspective of Chinese automotive market. It introduces a quantifiable Markov forecasting model that establishes the link between transition probabilities and penetration influencing factors. Through a penetration network, it visually represents the correlation and evolutionary states of AVs. Building upon the model, a framework for data quantification and analysis is formed. By quantifying model indicators with market data such as car performance and historical sales, the network parameters and transition probabilities are continuously updated in real-time. This drives the model to output short-term forecasts for AV penetration in the automotive market. In addition, we devise a two-stage simulation algorithm to accomplish parameter calibration and model validation. Through validation and comparative analysis, it is observed that, compared to direct learning from historical data, our model can more accurately forecast real market penetration trends. Furthermore, sensitivity analysis experiments on market strategies indicate that, compared to technical investment, the market exhibits a higher sensitivity to price adjustments. A strategy combination of increased technical investment in high-level vehicles and judiciously raising prices proves more advantageous for intelligent transformation in the automotive sector than a singular strategy. Additionally, as the AV market evolves, the sensitivity to favorable strategies will gradually increase. Therefore, the developmental stage of the market is a crucial factor for both car companies and investors to consider. The insights gleaned from this paper offer actionable guidance for policymakers and automotive corporations in shaping future market strategies, thereby fostering the continued growth of autonomous driving technologies within the industry. • Formulated a Markov forecasting model for autonomous vehicle market penetration. • Leveraged empirical vehicle data for robust model validation and calibration. • Explored strategic impacts for the automotive market's intelligence transition. [ABSTRACT FROM AUTHOR]

• Developed a dynamic model of a triple-evaporator domestic refrigerator/freezer. • Dynamic model validated within a 2 % deviation in average power consumption. • Implemented a two-stage economized cycle and its control scheme. • Achieved 12.9 % and 80 kWh/year reduction in power and energy consumption, respectively. • Estimated 18 TWh/year in global energy savings by 2030 with 10 % market penetration. Domestic refrigerator/freezers account for approximately 6 % of all energy consumption around the globe and mainly rely on vapor compression cycles to operate. Researchers have investigated alternative cycle architectures such as dual-loop cycles and parallel circuit cycles to improve their efficiencies. Despite the demonstrated energy saving potential of these advanced cycles, additional implementation costs are often not justifiable. However, to meet forthcoming stricter energy standards while ensuring flexible multi-temperature operation of domestic refrigerator/freezers, advanced cycle architectures are needed. In this paper, a state-of-the-art bypass circuit cycle triple-evaporator domestic refrigerator freezer with R-600a and a reciprocating compressor has been used as the baseline cycle investigate an alternative cycle configuration. Specifically, this work presents a two-stage vapor-injected cycle with a multi-evaporator system to enable energy savings and cost-effectiveness. The cycle establishes two separate evaporation temperatures to better match the cabinet temperature of fresh food and freezer compartment. The reduced difference between cabinet temperature and its evaporation temperature decreases the irreversibilities in the heat exchanger and improves overall system efficiency. Moreover, the addition of the economization line from the medium temperature evaporator reduces the compressor work. To capture the complex transient behavior of both the baseline system and proposed cycle architecture with their control strategies, a dynamic model has been developed and validated with experimental data. The validated dynamic model with the baseline cycle was modified to consider the two-stage vapor-injected cycle and its control logic, and simulation results yielded up to 13 % energy consumption reduction with respect to the baseline system. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive strategy for PT Sulzer Indonesia to expand its presence in the >400MW Steam Turbine market in Indonesia. Employing a mixed-method approach, the research combines qualitative interviews with six industry experts and quantitative Analytic Hierarchy Process (AHP) analysis to identify key success factors and prioritize Original Equipment Manufacturers (OEMs) for strategic marketing focus. The findings highlight the critical importance of market viability, particularly market accessibility, along with competitive advantages such as technological fit and strong engineering capabilities. The AHP analysis reveals Mitsubishi Hitachi Power Systems, Toshiba Energy Systems and Solutions, and GE Vernova as the top-ranked OEMs as potential focused market. A 12-month implementation plan is proposed, structured into six phases: preparation and assessment, planning and design, initial implementation, expansion, and refinement, further implementation, and evaluation and optimization. This plan emphasizes continuous learning, adaptability, and strategic alignment, drawing on established management theories and industry best practices. The study concludes that by focusing on these prioritized OEMs and following the proposed implementation plan, PT Sulzer Indonesia can effectively capitalize on the growing opportunities in the >400MW Steam Turbine market, leveraging its strengths while addressing challenges in resource alignment and market penetration. This research provides PT Sulzer Indonesia with a theoretically grounded and practically applicable roadmap for achieving sustainable growth and competitive advantage in this critical market segment. [ABSTRACT FROM AUTHOR]

We study how the U.S. government's anti-counterfeiting enforcement actions through Special 301 Reports influence U.S. businesses. We show that anti-counterfeiting enforcement in foreign countries improves U.S. firms' sales, profitability, and valuations. Firms significantly reduce capital and research and development investments when their brands and products are protected from counterfeiting activities. Anti-counterfeiting enforcement measures also improve brand asset value, brand profitability, brand inventiveness, market penetration, and customer loyalty. [ABSTRACT FROM AUTHOR]

The nexus between tourism and income inequality has received much attention but no consensus emerged. It is of interest to explore how this nexus is affected by the important external condition of the Internet. This study examines the spatial threshold effect of the Internet on the nexus between tourism and urban-rural income inequality by developing a spatial threshold model. Using panel data for 280 Chinese cities from 2003 to 2019, the results show that the impact of the Internet is characterised by clear spatial thresholds, and the local and spatial spillover effects of tourism on urban-rural income inequality vary under different regimes of Internet development. Further, by differentiating the Internet's functions, the inequality-reducing effect of tourism in local and surrounding cities has strengthened significantly as cities' Internet penetration improves; meanwhile, this effect has increased first and then decreased as cities' online market penetration deepens, with a relative optimal interval. [ABSTRACT FROM AUTHOR]

To alleviate the performance degeneration of the cooperative adaptive cruising control (CACC) of connected and automated vehicles (CAVs) with low market penetration rates (MPRs), it is necessary to resolve the performance degeneration of CAVs operating at weak mixed-platoon intensities for any-MPR CAVs. A car following model (PMCC) for CAVs is proposed, accounting for human reaction time, communication delay, traffic information memory, and vehicle-to-vehicle (V2V) communication. Linear stability analysis was conducted to validate the stability of mixed platoons at weak platoon intensities for different CAV following models. Numerical simulations were conducted to simulate weak-intensity mixed platoons for different CAV following models operating at high and low equilibrium velocities. The results suggest that PMCC exhibits wider stability equilibrium intervals under different theoretical time headway scenariosand performs well at dissipating the speed fluctuation propagation and minimizing the speed fluctuation amplitude. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) represent a significant development in the transport industry owing to their intelligent and interconnected features. Potential field theory has been extensively used to model CAV driving behaviour owing to its objectivity, universality, and measurability. However, existing car-following models do not consider the impact of time delays and the influence of information from multiple vehicles ahead and behind. This paper focuses on the driving-safety risks associated with CAVs, aiming to enhance vehicle safety and reliability during travelling. We developed a multi-vehicle car-following model based on safety potential fields (MIDM-SPF), taking into account the characteristics of multi-vehicle connected information and time delays. To enhance the model's precision, real-world data from urban roads were employed, alongside an improved optimisation algorithm to fine-tune the car-following model. The simulation experiment revealed that MIDM-SPF significantly reduces stop-and-go traffic, thereby improving traffic flow stability in urban areas. Additionally, we validated the stability of our model under varying market penetration rates in large-scale mixed traffic. Our findings indicate that increasing the CAV proportion improves the stability of mixed traffic flows, which has important implications for alleviating traffic congestion and guiding the large-scale implementation of autonomous driving in the future. [ABSTRACT FROM AUTHOR]

Current literature on joint optimization of intersection signal timing and connected automated vehicle (CAV) trajectory mostly focuses on vehicular movements paying no or little attention to pedestrians. This paper presents a methodology to safely incorporate pedestrians into signalized intersections with CAVs and connected human‐driven vehicles (CHVs). The movements of vehicles are controlled using both traffic lights and mobile CAV controllers during our newly introduced "white phase." CAVs navigate platoons of CHVs through the intersection when the white phases are active. In addition to optimizing CAV trajectories, the model optimally selects the status of the traffic light signal among white and green indications for vehicular and walk and do‐not‐walk intervals for pedestrian movements. A receding horizon‐based methodology is used to capture the stochastic nature of the problem and to reduce computational complexity. The case study results show the successful operation of fleets consisting of pedestrians, CAVs, and CHVs with various demand levels through isolated intersections. The results also show that increasing the CAV market penetration rate (MPR) can decrease average intersection delay by up to 27%. Moreover, the average pedestrian, CHV, and CAV delays decrease as the CAV MPR increases and reach their minimum values with a fully CAV fleet. In addition, the presence of the white phase can decrease the intersection average delay by up to 14.7%. [ABSTRACT FROM AUTHOR]

New Flexible Advertising Model Unveiled: Enhancing Advertising Strategies Researchers have generalized the classical Sethi advertising model (1983) to provide a flexible yet tractable approach to optimizing advertising strategies. Unlike traditional methods, the generalized Sethi advertising model is designed to adapt to different market conditions in various media and markets, offering advertisers greater flexibility. By assuming a constant-returns-to-scale relationship between advertising expenditure and untapped market potential, the generalized Sethi advertising model provides advertisers with more options without sacrificing tractability. The research team has made important breakthroughs by developing practical formulas for determining the best advertising strategies for both individual companies and groups of companies. They have also conducted analyses to better understand how different factors influence these strategies. The generalized Sethi advertising model opens up new opportunities for advertisers to fine-tune their campaigns and reach more customers. This research marks a significant step forward in advertising optimization, giving businesses a valuable tool to achieve better results and make informed decisions in their advertising efforts. We propose a flexible yet tractable dynamic advertising model called the generalized Sethi model to capture different market penetration rates across various media and markets via advertising. Specifically, the generalized Sethi model employs a Cobb–Douglas production function of advertising expenditure and the untapped market share with constant returns to scale. It encompasses some standard dynamic advertising models as particular cases. Moreover, the model's flexibility does not compromise its tractability. We demonstrate it by showing single- and multifirm advertising problems involving Nash and Stackelberg games to admit closed-form expressions for the firms' optimal advertising strategies and value functions under the generalized model. Sensitivity analysis of the model parameters also yields novel economic insights regarding the firms' optimal advertising strategies and value functions. Funding: A. P. Kennedy acknowledges the Hong Kong University Grant Council for their support of him pursuing his PhD at the Chinese University of Hong Kong. S. P. Sethi acknowledges financial support from the Eugene McDermott Chair Professorship. C. C. Siu acknowledges financial support from the Research Grants Council of Hong Kong [Grant "Generalized Sethi Advertising Model and Extensions" (Project UGC/FDS14/P02/20)]. S. C. P. Yam acknowledges financial support from HKGRF-14301321 [Project "General Theory for Infinite Dimensional Stochastic Control: Mean Field and Some Classical Problems] and General Research Fund by the Research Grants Council of Hong Kong-14300123 [Project "Well-Posedness of Some Poisson-Driven Mean Field Learning Models and Their Applications"]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2021.0717. [ABSTRACT FROM AUTHOR]

Concentrated solar power (CWP) technology has matured sufficiently for large‐scale implementation. In a typical plant, the solar energy is captured by mirrors and directed onto heat‐transfer fluid (HTF), typically a molten salt that is further conveyed to the thermal energy‐storage system before being channeled to power turbines, generating electricity. A major concern about this technology is the need to reduce the levelized cost of electricity, necessitating heightened efficiency to enhance cost competitiveness and foster greater market penetration. One approach to achieve this involves replacing the current nitrate‐based molten salt mixture with nanofluids. They combine nitrate‐based molten salt and small amounts of nanomaterials of different dimensionality. These promising HTFs present a superior performance concerning their physical, thermal, and chemical properties. However, there is a lack of studies related to understanding the effects of nanomaterials and the underlying enhancement theories. Therefore, in this article, a detailed revision of the state of the art in experimental and theoretical studies of nanomaterials in a binary commercial nitrate‐based molten salt (solar salt) as HTF for CWP plants is presented, highlighting the challenges related to their application and future research directions. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) are being developed and designed to operate on existing roads. Their safe and efficient operation during roadworks, where traffic management measures are often introduced, is crucial. Two alternative measures are commonly applied during roadworks on motorways: (i) closing one or multiple lanes (ii) narrowing one or all lanes. The former can cause delays and increased emissions, while the latter can pose safety risks. This study uses a VISSIM‐based traffic microsimulation to compare the effectiveness of these two strategies on traffic efficiency and safety, considering various market penetration rates (MPR) of CAVs. The model was calibrated and validated with the data collected from M1 motorway in the United Kingdom. Results show that average delays per vehicle‐kilometre‐travelled decreased from 102.7 to 2.5 s (with lane closure) and 23.6 to 0.6 s (with narrow lanes) with 0% and 100% CAV MPR, respectively. Moreover, safety in narrow lanes improved by 4.8 times compared to 1.5 times improvement in lane closure with a 100% CAV MPR; indicating that narrow lanes would result in better safety performance. These findings could assist transport authorities in designing temporary traffic management measure that results in better CAV performance when navigating through roadworks. [ABSTRACT FROM AUTHOR]

Copyright of Automotive Digest is the property of Automotive Digest Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The widespread adoption of Connected and Automated Vehicles (CAVs) is being propelled, not only in the realm of private vehicles but also within transit systems. This development serves to enhance urban transport activities, rendering transportation more appealing to passengers. The present study aims to identify and examine the safety effects of testing different operational speed shuttle bus services in various future mobility conditions. To investigate impacts of autonomous shuttle bus services and to further examine their operational speed, the microscopic simulation method was performed. Specifically, four sets of simulation scenarios were comprised: a baseline scenario representing the current conditions and three operational speed scenarios (15 km/h, 30 km/h and 45 km/h) for an autonomous shuttle service. Each one of these sets included eleven CAV market penetration rates (MPRs) of CAVs of the general traffic (ranging from 0 to 100% in 10% increments). By analyzing the trajectory data extracted from microsimulation, traffic conflicts were identified and further analyzed by developing Mixed-Effects Multinomial Logit Regression models (ME-MLMs) in order to associate conflict type taking into account network characteristics as well as traffic conditions. Several aspects were determined as statistical significant parameters influencing type of conflict. The analysis yielded several significant findings that provide quantitative measurements and assessments of the effects observed, enabling a better understanding of the safety implications associated with the widespread adoption of automated services. [ABSTRACT FROM AUTHOR]

Organic photovoltaic (OPV) technology has recently achieved remarkable progress in academia, attaining power conversion efficiencies exceeding 19%, a breakthrough previously unimaginable. Despite these advancements, the translation of high‐efficiency OPV cells into the commercialization of OPV modules has been limited, impeding the market penetration of OPV technology. Upon careful examination, various challenges emerge, including disparities between laboratory research and industrial production in device architecture, influenced by considerations of cost and manufacturability. Additionally, the incorporation of high‐efficiency materials requires careful consideration not only of the compatibility between the photoactive layer and interface layers or transparent electrodes but also of the associated synthetic complexity of chemical structures and cost implications. While these issues are crucial, they may not be widely discussed in current mainstream research. In this article, the purpose is to identify bottlenecks from a material techniques perspective, with the aim of promoting increased resources in the research of pertinent module technologies. This effort is intended to propel OPV technology toward greater success and bring it into closer alignment with the goals of commercialization. [ABSTRACT FROM AUTHOR]

Mobile devices and handheld systems, such as the smartphones and tablets universally extended, are becoming increasingly powerful. Their basic hardware configuration is usually state-of-the-art heterogeneous architectures consisting of multi-core processors and some kind of accelerator such as GPUs or DSPs. Specific code adapted to the architecture is mandatory if high-performance computation is required and low-level libraries and parallelism are needed, which constitutes an important barrier for the usual developer in such devices. In this context, we propose the FancyJCL framework. It provides a high-level abstraction layer that hides implementation details and allows to develop parallel programs for mobile devices. The target platform for FancyJCL is mainly Android and Java developers due to their high market penetration. A very simple, seemingly sequential encoding results in parallel efficient OpenCL code. FancyJCL is itself based on the Fancier framework, which enables optimal memory management across memory spaces on unified memory systems. Benchmarks of FancyJCL code developed for a wide range of image processing algorithms show good performance with low development effort. [ABSTRACT FROM AUTHOR]

Biochar production through slow pyrolysis is a versatile and adaptable approach for managing diverse biomass waste. However, their industrial applications remain limited because of their high energy consumption and the emission of toxic gases. Solar-biomass pyrolysis systems have been proposed to address these challenges. This review examines the relationship between output configuration and the adaptability of slow and solar-biomass pyrolysis systems for biochar production. Studies have revealed that the average heat energy required for thermal conversion of biomass to biochar ranges from 1.94 to 2.67 kJ/kg K can be achieved through both conventional and solar pyrolysis routes. Solar pyrolysis demonstrates maximum power and flux density of 1.5 kW and 12,000 kW/m2, respectively, aligning with the power and temperature range of conventional slow pyrolysis. Moreover, solar pyrolysis emits approximately 58.89% less CO2 as compared to the conventional electrical heating-based pyrolysis. Despite these advantages, the market implementation of solar-biomass pyrolysis systems is limited, necessitating the resolution of various barriers for commercial applications. The current review concludes by providing future recommendations, emphasizing the development of an eco-friendly solar-biomass pyrolysis system for large-scale biochar production. [ABSTRACT FROM AUTHOR]

Induction heating is an efficient and high-performance heating method which already has a significant market penetration and economic impact due to its benefits inherent to contactless energy transfer systems such as quickness, cleanness, and safety. Efficiency is a key design parameter since it determines not only the appliance performance but also its environmental impact, with significant socio-political implications. However, it is not easy to determine and compare the actual power converter efficiency operating under highly variable conditions typical of IH. This paper proposes an averaged efficiency parameter elaborated based on technical and typical IH usage conditions that offers a useful value to compare power converters operating under realistic operation conditions. The proposed parameter has been evaluated in some of the most significant power converter topologies used in reported state-of-the-art induction heating systems. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The lack of real-world data on Connected and Autonomous Vehicles (CAVs) has prompted researchers to rely on simulations to assess their societal impacts. However, few studies address the operational and technological challenges of integrating CAVs into existing transport systems. This paper introduces a new CAV driving model featuring a constant time gap longitudinal control algorithm that accounts for sensor errors and platoon formations of varying sizes. Additionally, it develops a high-level route-based decision-making algorithm for CAV path choice. These algorithms were tested in a calibrated motorway corridor simulation, examining different market penetration rates, platoon sizes, and sensor error scenarios. Traffic conflicts were used as a primary safety performance indicator. The findings indicate that CAV sensors are generally adequate, but optimal platoon sizes vary with market penetration rates. To further explore factors influencing traffic conflicts, a hierarchical Bayesian negative binomial regression model was used. This model revealed that in addition to unobserved heterogeneity and spatial autocorrelation, the standard deviation of speeds between lanes and the CAV market penetration rate significantly affect conflict occurrences. These results corroborate the simulation outcomes, enhancing our understanding of CAV deployment impacts on traffic safety. [ABSTRACT FROM AUTHOR]

In this paper, we consider a novel reliability-based network equilibrium problem for mixed traffic flows of human-driven vehicles (HVs) and connected autonomous vehicles (CAVs) with endogenous CAV market penetration and stochastic link capacity degradations. Travelers' perception errors on travel time and their risk-aversive behaviors on mode choice and path choice are incorporated in the model with a hierarchical choice structure. Due to the differences between HVs and CAVs, the perception errors and the safety margin reserved by risk-averse travelers are assumed to be related to the vehicle type. The path travel time distribution is derived by using the moment-matching method based on the assumption that link capacity follows lognormal distribution and link travel times are correlated. Then, the underlying problem is formulated as an equivalent variational inequality problem. A path-based algorithm embedded with the Monte Carlo simulation-based method is proposed to solve the model. Numerical experiments are conducted to illustrate the features of the model and the computational performance of the solution algorithm. [ABSTRACT FROM AUTHOR]

The research was conducted with the aim of finding innovations in designing business development strategies oriented to the external and internal conditions of the Panca Wargi Group. The approach chosen is a qualitative methodology that utilises primary and secondary data types in obtaining information. Interviews were conducted with fourteen interviewees, namely the group leader, core management, and group members. In this strategy planning, the IFE Matrix and EFE Matrix have outlined the internal and external aspects of the group as a basis for strategy design. Based on the results of the Internal and External Matrix (IE), it is found that the condition of the group is in position V which leans towards market penetration and product development strategies with the aim of maintaining stable business growth. The V position of the panca wargi fish group indicates that the internal and external aspects have almost equal strength, which in the losng run will lead to stagnant business development, which may turn out to be dangerous in the future. With the use of the TOWS Matrix and QSPM Matrix, the twelve best alternative strategies have been compiled based on the TAS value to optimise the use of strategies. Panca Wargi Fish Group can get the best business development results starting from having the right strategy formulation. [ABSTRACT FROM AUTHOR]

Today there are companies experimenting with autonomous mobile vehicle and equipment technologies. These technologies come in various forms, from small delivery robots to large automated heavy-duty trucks and cargo movers. Some of these have been part of the labor force in factories, warehouses, and distribution centers worldwide for some industries, and their expansion is likely. A recent white paper from UC Davis assesses the landscape for freight automation and its potential labor impacts in the freight and warehousing sector; this policy brief summarizes the key findings and policy implications of that research. While there are still more questions than answers, it is known that as the technology matures, the future for workers will depend on policymaker and industry actions. While these actions can have potentially negative effects for some workers (e.g., job loss or reduced job quality), they can have positive effects for others (e.g., improved safety, security, job quality, and new high-quality jobs).View the NCST Project Webpage

The expansion of automation in the U.S. economy is increasingly tangible and will presumably entail positive and negative impacts that are not yet well understood. In the freight sector, there is uncertainty about how and when automation will impact labor. Beyond this, there are further unknowns about what the impacts will be on such freight subsectors as warehousing, long- and short-haul. It is expected that penetration rates of freight automation will vary across subsectors. In some subsectors, new jobs will be created and/or working conditions will improve. Other subsectors will see declining job quality and/or job losses that require workers to transition to new roles or sectors entirely, when possible. Changes in job opportunities and quality will vary within sectors and subsectors, by region, and/or by firm. This study offers an overview and recommendations in three directions. First, despite the uncertainties and based on past and present examples of automation, it provides some insights about strategies that may help impacted workers within and outside of the heavy freight sector transition. Second, it discusses examples of existing public policies that can support a transition for automation-impacted workers. And third, it provides insights on how different freight subsectors are likely to be impacted by automation.View the NCST Project Webpage

In just a few years motorcycles had become an irreplaceable object for the daily life of Indigenous people in the Gran Chaco region. In spite of their pervasiveness, there are still many aspects to this current dissemination that remain to be unraveled. This paper explores the ways in which motorcycles have been incorporated into Indigenous material culture and the ways they are reshaping Indigenous perceptions and relations with the local environment. Starting from the machines and their uses is a way to not confine Indigenous people to a position as victims of modernity, but rather to recognize their proactive role in the ongoing reproduction and transformation of their cultural world. For this purpose, I take the example of the Wichí fishery to see how this cultural practice is changing as fishermen adopt motorcycles as means of transport. I investigate this practice and its transformations based on ethnographic fieldworks carried out with several communities settled on the banks of the Pilcomayo River, as well as readings of the ethnological literature which contains detailed descriptions of this practice. By tracing its past and ongoing transformations, I show how the hold and spatial organization of Wichí fishery has evolved as motorcycles spread to the whole Pilcomayo area. Their adoption redefines fishermen perceptions and relations with the surrounding environment, which is now understood from a new mechanized and motorized perspective of capitalization and exploitation. Indeed, while motorcycles allow them to integrate into the market, they further promote market penetration on Indigenous lands. At the same time, I demonstrate how motorcycles allow fishermen to overcome the inconveniences of an intractable river and new infrastructures that hinder fishing practices, as well as to bypass the attempts to privatize the riverbanks. In a way, the fishermen are more resilient to these sudden changes thanks to motorcycles. [ABSTRACT FROM AUTHOR]

Due to recent advancements in connected and autonomous vehicles (CAVs), freeway traffic control (FTC) has become a trendy area of research. Combining CAVs and control measures has opened more efficient traffic flow possibilities. However, while there is extensive research on how traffic control and CAVs can enhance traffic flow performance, their safety benefits should be evaluated more comprehensively. It is challenging to distinguish their contributions to traffic flow safety. Studies on the safety of CAVs in traffic flow indicate that traffic flow safety improves with higher market penetration rates (MPR) of CAVs. However, this finding only sometimes aligns with the traffic flow performance effects of CAVs on freeways. This paper introduces a framework for assessing the safety effects of FTC strategies in mixed traffic scenarios involving human-driven vehicles and CAVs. The proposed framework is tested through a microsimulation-based case study in Istanbul, Turkey. The results show that, despite varying MPRs, the safety effects of CAVs and FTC methods do not consistently reduce the number of conflicts in the traffic flow context. [ABSTRACT FROM AUTHOR]

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This study presents a decision-support methodology to design and optimize modular Boost converters in the context of fuel-cell electric vehicles. It involves the utilization of interleaved techniques to reduce fuel-cell current ripple, enhance system efficiency, tackle issues related to weight and size concerns, and offer better flexibility and modularity within the converter. The methodology incorporates emerging technologies by wide-bandgap semiconductors, providing better efficiency and higher temperature tolerance. It employs a multiphysical approach, considering electrical, thermal, and efficiency constraints to achieve an optimal power architecture for FCHEVs. Results demonstrate the advantages of wide-bandgap semiconductor utilization in terms of volume reduction and efficiency enhancements for different power levels. Results from one of the considered power levels highlight the feasibility of certain architectures through the utilization of WBG devices. These architectures reveal improvements in both efficiency and volume reduction as a result of incorporating WBG devices. Additionally, the analysis presents a comparison of manufacturing cost between standard and wide-bandgap semiconductors to demonstrate the market penetration potential. [ABSTRACT FROM AUTHOR]

Authors explore the role of human capital in organic agriculture in Serbia. Through semi-structured interviews with 64 individual farmers holding organic production certificates, key aspects of human capital, including education level, language proficiency and ICT usage were analyzed. Findings reveal a disparity between conventional and organic farming in terms of computer literacy and ICT utilization, underscoring the need for targeted interventions to enhance technological adoption in organic farming. Moreover, the study identifies the importance of membership in agricultural associations for organic farmers, facilitating knowledge exchange and market penetration. The results suggest that human capital plays a pivotal role in driving advancements in organic agriculture, with implications for the sustainability and growth of the sector in Serbia. This underscores the necessity for future research to go deeper into human capital dynamics and their implications for sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Introduction: Biosimilars offer a cost-effective alternative to original biopharmaceuticals with comparable efficacy and safety. The perception and familiarity of prescribers toward biosimilars play a critical role in their market penetration. Yet, few studies have explored the perception of oncologists toward biosimilars, much less in Asia. Objectives: The objective of this study is to understand barriers of adopting biosimilars among oncologists and explore strategies to promote their use in clinical practice settings. Methods: A web-based survey was conducted among Korean oncologists from September to October 2022, assessing their perception of biosimilars and prescribing practices. Results: Among the 118 surveyed oncologists, 75.4% (89 out of 118) had previously prescribed biosimilars. When asked about their preference, 48.3% (57 out of 118) of the respondents preferred originators to biosimilars, whereas 16.1% (19 out of 118) favored biosimilars over the originators. The primary reason for preferring the originators was trust in safety and efficacy (94.7%, 54 out of 57). Still, a paradox was noted as 87.0% (47 out of 54) and 85.2% (46 out of 54) of these also acknowledged the comparable efficacy and safety of biosimilars. A relatively small number of the respondents (16.1%, 19 out of 118) did not consider prescribing biosimilars to biologic-naïve patients at all, and up to 56.8% (67 out of 118) expressed reluctance to switch prescriptions from originators to biosimilars. However, 90.7% (107 out of 118) of respondents considered changing their prescription to biosimilars if patients faced financial stress. Concerns regarding the efficacy when switching to biosimilars were expressed by 42.7% (38 out of 89) of oncologists with biosimilar prescribing experience, increasing to 69.0% (20 out of 29) among those without such experience. Conclusion: Korean oncologists perceived biosimilars to be as safe and effective as originators. However, there is a notable mismatch between this perception and their prescribing practices, particularly among those who have not prescribed biosimilars before. The financial burden of patients served as a significant driver for prescribing biosimilars, yet marginal price differences between originators and biosimilars may be associated with the low adoption rate of biosimilars in Korea. Active price competition may enhance market penetration of biosimilars. [ABSTRACT FROM AUTHOR]

The article focuses on intervention research as a design science that devises action to change existing situations. Topics include market penetration strategies using intervention research, dysfunctions in the import and distribution of agricultural nutrients, and recommendations for developing effective market strategies based on lived market realities.

The spectrum of Internet of Things (IoT) applications is vast. It serves in various domains such as smart homes, intelligent buildings, health care, emergency response, and many more, reflecting the exponential market penetration of the IoT. Various security threats have been made to modern-day systems. Cyberattacks have seen a marked surge in frequency, particularly in recent times. The growing concern centers around the notable rise in cloning attacks, persisting as a significant and looming threat. In our work, an in-depth survey on the IoT that employs physically unclonable functions (PUFs) was conducted. The first contribution analyzes PUF-based authentication, communication protocols, and applications. It also tackles the eleven challenges faced by the research community, proposes solutions to these challenges, and highlights cloning attacks. The second contribution suggests the implementation of a framework model known as PUF3S-ML, specifically crafted for PUF authentication in the Internet of Things (IoT), incorporating innovative lightweight encryption techniques. It focuses on safeguarding smart IoT networks from cloning attacks. The key innovation framework comprises three stages of PUF authentication with IoT devices and an intelligent cybersecurity monitoring unit for IoT networks. In the methodology of this study, a survey relevant to the concerns was conducted. More data were provided previously regarding architecture, enabling technologies, and IoT challenges. After conducting an extensive survey of 125 papers, our analysis revealed 23 papers directly relevant to our domain. Furthermore, within this subset, we identified 11 studies specifically addressing the intersection of communication protocols with PUFs. These findings highlight the targeted relevance and potential contributions of the existing literature to our research focus. [ABSTRACT FROM AUTHOR]

The emergence of connected autonomous vehicles (CAVs) has the potential to dramatically increase road capacity, and the provision of dedicated lanes for CAVs is a common management strategy to ensure that CAVs take appropriate priority over other vehicles. However, existing models of CAV lane management do not perform well at low CAV market penetration rates. Therefore, a novel model is proposed to address this shortcoming in this paper, and qualified human‐driven vehicles (HDVs) are allowed to enter the CAV priority lane when there is a low CAV penetration rate. A theoretical model is proposed to examine the impacts of three managed lane strategies under mixed traffic and then compare three lane management strategies under different CAV penetration rates and traffic demands. The results show that these lane management strategies can improve throughput, reduce travel time, increase speed, and reduce the variance of the distribution of vehicle speeds under different penetration rates and traffic demands. [ABSTRACT FROM AUTHOR]

This research aims to determine marketing strategies that can be implemented to improve marketing performance at Zeribowl Dessert using the SWOT analysis method. This research method uses a qualitative method with a descriptive approach with data collection methods through documentation studies, observations, interviews and questionnaires obtained from 30 customers and 4 Zeribowl Dessert staff. The research results show that the Strength and Opportunities (SO) value is 3.23. Then the Weakness and Threats (WT) value is 3.6. Thus the researcher concludes that an aggressive strategy can be carried out by maximizing strength by taking advantage of Zeribowl's opportunities to gain profits through marketing strategies that can be implemented by Zeribowl Dessert, including; market development and market penetration, product development, market target and market positioning. [ABSTRACT FROM AUTHOR]

Internal combustion engine vehicles (ICEs), hybrid, plug-in hybrid and battery electric vehicles (HEVs, PHEVs, and BEVs) represent tradition, high technology, energy conservation and innovation respectively. The new energy vehicles (NEVs) include PHEVs and BEVs. This study innovatively proposes an agent-based real-time game model to simulate the market penetration of vehicles in China. The advantage of the model is in accord with the product diffusion theory and synchronous with the cognition of consumers. The purchase preference is described by a hierarchical variables structure, which forms a probit model with the approximately normal distribution based on the central limit theorem. The results show that when the individual purchase of ICEs will not bring any incentive for others to purchase ICEs, the market penetration of ICEs will decrease. The development of NEVs should focus on their own competitiveness, and the interaction between the proven technology of ICEs and the rapid development of NEVs is useful for NEVs. Restricted with the narrow price range, the market penetration of HEVs will keep steady. Finally, the high interaction frequency is good for NEVs, which indicates that WeMedias will play an important role.

Fighting climate change has become a major task worldwide. One of the key energy sectors to emit greenhouse gases is transportation. Therefore, long term strategies all over the world have been set up to reduce on-road combustion emissions. In this context, the road freight sector faces significant challenges in decarbonization, driven by its limited availability of low-emission fuels and commercialized zero-emission vehicles compared with its high energy demand. In this work, we develop the Mobility and Energy Transportation Analysis (META) Model, a python-based optimization model to quantify the impact of transportation projected policies on freight transport by projecting conventional and alternative fuel technologies market acceptance as well as greenhouse gas (GHG) emissions. Along with introducing e-fuels as an alternative refueling option for conventional vehicles, META investigates the market opportunities of Mobile Carbon Capture (MCC) until 2050. To accurately assess this technology, a techno-economic analysis is essential to compare MCC abatement cost to alternative decarbonization technologies such as electric trucks. The novelty of this work comes from the detailed cost categories taken into consideration in the analysis, including intangible costs associated with heavy-duty technologies, such as recharging/refueling time, cargo capacity limitations, and consumer acceptance towards emerging technologies across different regions. Based on the study results, the competitive total cost of ownership (TCO) and marginal abatement cost (MAC) values of MCC make it an economically promising alternative option to decarbonize the freight transport sector. Both in the KSA and EU, MCC options could reach greater than 50% market shares of all ICE vehicle sales, equivalent to a combined 35% of all new sales shares by 2035.

Carbon emissions targets require large reductions in greenhouse gases (GHGs) in the near-to mid-term, and the transportation sector is a major emitter of GHGs. To understand potential pathways to GHG reductions, this project developed the U.S. Transportation Transitions Model (US TTM) to study various scenarios of zero-emission vehicle (ZEV) market penetration in the U.S. The model includes vehicle fuel economy, vehicle stock and sales, fuel carbon intensities, and costs for vehicles and fuels all projected through 2050. Market penetration scenarios through 2050 are input as percentages of sales for all vehicle types and technologies. Three scenarios were developed for the U.S.: a business as usual (BAU), low carbon (LC), and High ZEV scenario. The LC and High ZEV include rapid penetration of ZEVs into the vehicle market. The introduction of ZEVs requires fueling infrastructure to support the vehicles. Initial deployments of ZEVs are expected to be dominated by battery electric vehicles. To estimate the number and cost of charging stations for battery electric trucks in the mid-term, outputs were used from a California Energy Commission (CEC) study projecting the need for chargers in California. The study used the HEVI-Pro model to estimate electrical energy needs and number of chargers for the truck stock in several California cities. The CEC study outputs were used along with the TTM model outputs from this study to estimate charger needs and costs for six U.S. cities outside California. The LC and High ZEV scenarios reduced carbon emissions by 92% and 94% in the U.S. by 2050, respectively. Due to slow stock turnover, the LC and High ZEV scenarios contain significant numbers of ICE trucks. The biomass-based liquid volume reaches 70 (High ZEV) to 80 (LC) billion GGE by 2045. For the cities in this study, the charger cost ranges from $5 million to $2.6 billion in 2030 and from roughly $1 billion to almost $30 billion in 2040.View the NCST Project Webpage