Search Results (9)

Thin-film thermoelectric generators (TFTEGs) emerge as critical components of self-sustaining agricultural systems because they can utilize temperature gradients to generate plant-transpiration-induced thermovoltage signal quantifiable to plant health status. This study examines the latest developments in TFTEG materials, device structures, manufacturing processes, and their integration into agricultural systems such as plant-wearable, canopy-level and stem-clipped TEGs. Key questions addressed include the ideal materials for TFTEG fabrication, their biocompatibility and eco-stability in agricultural settings, recent design and AI-assisted optimization advancements, and future research directions in non-conventional TEG applications. The analysis consolidates evidence from inorganic, organic, and hybrid thermoelectric materials with respect to performance in terms of flexibility, thermal stability, output power, and biocompatibility. Bibliometric analysis was employed to determine dominant research topics and gaps, especially with respect to sustainability and AI-augmented design. The review emphasizes the latest breakthroughs in structural optimization, flexible substrates, encapsulation strategies, and sensor integration for reliability enhancement in field environments. In addition, applications of AI, including neural network-based conditional Generative Adversarial Network, surrogate modeling, and multi-objective optimization, are discussed in relation to the improvement of thin-film TEG design and simulation processes. This study suggests that TFTEGs exhibit great potential in agricultural monitoring and plant wearable applications but material toxicity, mechanical degradation, and integration with AI are still major obstacles. Full article

This paper describes a range of Paleozoic and Mesozoic mosses and assesses how far they can be referred to extant taxa at the family, ordinal, or class levels. The present study provides new data on Paleozoic mosses of the order Protosphagnales, re-evaluating affinities of some groups previously thought to be unrelated. The leaf areolation pattern, combined with the leaf costa anatomy, results in the subdivision of Protosphagnales into five separate families: Protosphagnaceae (at least six genera), Polyssaieviaceae (at least three genera), and three monogeneric families: Rhizonigeritaceae, Palaeosphagnaceae, and Servicktiaceae. We urge caution in referring Paleozoic and Early Mesozoic fossil mosses as members of Dicranidae and Bryidae, as they may belong to the extinct moss order Protosphagnales. Additional evidence supports the relation of the Permian genus Arvildia to extant Andreaeopsida. We segregate Late Palaeozoic and Early Mesozoic mosses that are superficially similar to extant members of either Dicranales or Polytrichales, into the artificial informal group of Archaeodicranids, distinguishing them from ecostate Paleozoic and Mesozoic mosses, which are combined here into another artificial informal group, Bryokhutuliinids. The latter includes the genus Bryokhutuliinia, widespread in contemporary Asia, from the Middle Jurassic to the Lower Cretaceous, as well as other superficially similar ecostate plants from different regions worldwide, ranging from the Upper Palaeozoic to the Lower Cretaceous. A list of Paleozoic, Mesozoic, and Eocene moss fossils suitable for age calibration in phylogenetic trees is provided. Full article

With the progress of globalization, the environment for enterprises’ survival and development has become increasingly complex. More and more enterprises realize that their sustainable competitive advantage is closely related to the development of enterprise niche. Based on the ecostate-ecorole theory, an evaluation index system for enterprise niche is developed in this paper. The study selects indicators based on literature research and frequency analysis, adopts factors including market environment, industrial environment, human resources, and technical resources to evaluate ecostate of enterprise niche, and establishes an evaluation model for ecostate; the research uses factors including policy environment, innovation decision-making ability, resource accessibility, and technical management capability to evaluate ecorole of enterprise niche, and sets up an evaluation model for ecorole by catastrophe progression method. The results of the reliability and validity test showed that the evaluation index system is both reliable and effective. The paper provides implications for the evaluation of enterprise niche. Full article

Aiming at the problem that the current dynamic economic dispatch (DED) fails to consider the response risk of spinning reserve caused by the fluctuation and uncertainty of wind power, we work out a DED problem considering time-coupling spinning reserve response risk while the stochasticity and variability arising from RESs are taken into consideration. The developed framwork unified the response risk of reserve caused by forced shutdown of the unit into the response risk caused by time coupling. The expected customer interruption cost (ECOST) and the expected abandoned wind cost considering this reserve response risk are added to the objective function. While seeking the minimum objective function, the system is automatically configured with suitable reserve to ensure the consistency of the system’s response risk in each period. An improved multi-universe parallel quantum genetic algorithm was used to solve the model. Numerical examples and analysis prove the effectiveness and feasibility of the proposed method. Full article

Green innovation is an important driving force in promoting the sustainable development of manufacturing enterprises and improving market competitiveness. This study selects indicators from the two aspects of ecostate and ecorole in order to reflect green research and development, cleaner production, and green marketing based on niche theory. We construct an evaluation index system to objectively and accurately assess the green innovation capability of manufacturing enterprises. Subsequently, based on the principle of relative entropy, the analytic hierarchy process, entropy weight method, and coefficient of variation method are fused to determine the combined weight of the indicators, and a multi-level, comprehensive evaluation model is constructed using cloud model tools. Finally, through an empirical analysis of the evaluation of the green innovation capability of five manufacturing enterprises, the feasibility of the model and the stability of the evaluation results are verified through three dimensions: numerical experiment, sensitivity analysis, and method comparison. The results show that the evaluation system constructed in this study is superior. It provides the basis and decision-making reference for enterprises to carry out market positioning and formulate innovation and development strategies. Full article

Transitioning from high school to university presents a significant challenge for many students on multiple fronts, including language learning. This mixed-method study draws on an ecological perspective to investigate students’ English learning experiences during the transition from high school to university in China, focusing on teaching content, teaching approach, assessment and feedback, and self-regulated learning. Data is collected from six universities at three different academic levels in China, and analyzed using both statistical and thematic analysis. The research finds that there are differences between high school and university English language education in the above-mentioned four areas, and students’ ecopotentials are of critical importance for their adaptation to university English learning. These findings suggest the necessity of the continuity of teaching content, the promotion of individualized curricula, and the cultivation of self-regulated learning capacities to support students’ sustainable English learning during the transition from high school to university. Full article

Reliability is an important index which determines the power service and quality provided to customers. As the demand increases continuously and the system changes in accordance with the environmental regulation, the reliability assessment in the distribution system becomes crucial. In this paper, we propose methods for improving the reliability of the distribution system using electric vehicles (EVs) in the system. In this paper, EVs are used as power supplying devices, such as a transportable energy storage system (ESS) which supplies power when fault occurs in the system, and by using a time–space network (TSN) in particular, EV capacity in accordance with the load arrival time was calculated. Unlike other existing reliability assessments, we did not use the average load of customers. Instead, by taking into account the load pattern by times, we considered the priority for load supply in accordance with the failure scenarios and failure times. Based on the priority calculated for each time of failure and failure scenario, plans for EV operation to minimize expected customer interruption cost (ECOST), the reliability index in the distribution system, were established. Finally, a case study was performed using the IEEE RBTS (Roy Billinton Test System) 2 Bus and the performance of the model proposed in this paper was verified based on the result. Full article

A two-level optimization method is presented to find the optimal number and location of conventional protective devices to be upgraded to remote-controlled switches (RCSs) for an existing distribution network (DN). The effect of distributed generation (DG) on this problem is considered. In the first level, a nonlinear binary program is proposed to maximize the restored customers subject to technical and topological constraints. All feasible interchanges between protective devices and ties involved in the restoration, when a fault occurs at all possible locations are found considering switching dependencies. In the second level, a nonlinear cost function, combining the expected cost of interruptions (ECOST) and the switch cost, is minimized with respect to the location of RCSs. The expected cost function is computed based on the optimum restoration policies obtained from the first level. The optimum placement of RCSs using the proposed algorithm is tested on a 4-feeder 1069-node test system and compared to the solution obtained with a genetic algorithm (GA) on the same system. Full article

The objective of this study is to understand which requirements for cereal cultivars—with regard to climate change adaptation—are in demand by farmers and advisors, and to clarify whether there are any differences in their assessments. A comparative survey was used to collect data from 410 farmers and 114 advisors in Germany. The majority of both farmers and advisors reported perceivable effects of climatic change on plant production. The increase in droughts and hot spells, the increased incidence of torrential rain, and mild winters were mentioned as the main effects of climate change. For climate change adaptation, the farmers and advisors mostly relied on a locally-adapted cultivar selection. It is estimated that eco-stability, grain yield, resistance to lodging and drought tolerance are important cultivar properties. In the study, farmers and advisors equally pointed out the need for additional cultivar evaluation according to eco-stability. Finally, only minor differences regarding farmers’ and advisors’ assessments were found within the study. The outcome of this research points to the need of implementing farmers’ demands in cultivar recommendations. For example, an impartial assessment of cultivars’ eco-stability could help support the choice of cultivars and reduce the growing risks in cereal production with regard to climate change. Full article