An enhanced genetics × environment × management framework for yield intensification
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Subtropical western boundary currents (WBCs) refer to swift narrow oceanic currents that flow along the western edges of global subtropical ocean basins. Earlier studies indicated that the WBCs are extending poleward under a warming climate. However, owing to limited observations and coarse resolution of climate models, how greenhouse warming may affect the zonal structure of the WBCs remains unknown. Here, using seven high-resolution climate models, we find an onshore intensification of the WBCs in a warming climate. The multimodel ensemble mean of onshore acceleration ranges from 0.10 ± 0.08 to 0.51 ± 0.24 cm s−1 per decade over 1950–2050. Enhanced oceanic stratification associated with fast surface warming induces an uplift of the WBCs, leading to the projected change. The onshore intensification could induce anomalous warming that exacerbates coastal marine heatwaves, reduces ability of the coastal oceans to absorb anthropogenic carbon dioxide and destabilizes methane hydrate stored below the sea floor of shelf regions.
Artificial intelligence in clinical genetics
Artificial intelligence (AI) has been growing more powerful and accessible, and will increasingly impact many areas, including virtually all aspects of medicine and biomedical research. This review focuses on previous, current, and especially emerging applications of AI in clinical genetics. Topics covered include a brief explanation of different general categories of AI, including machine learning, deep learning, and generative AI. After introductory explanations and examples, the review discusses AI in clinical genetics in three main categories: clinical diagnostics; management and therapeutics; clinical support. The review concludes with short, medium, and long-term predictions about the ways that AI may affect the field of clinical genetics. Overall, while the precise speed at which AI will continue to change clinical genetics is unclear, as are the overall ramifications for patients, families, clinicians, researchers, and others, it is likely that AI will result in dramatic evolution in clinical genetics. It will be important for all those involved in clinical genetics to prepare accordingly in order to minimize the risks and maximize benefits related to the use of AI in the field.
Sustainable supply chain management practices and performance: The moderating effect of stakeholder pressure
Currently, sustainable supply chain management practices have become an important strategy for firms to improve performance and gain competitive advantage. However, there is a current debate over the performance outcomes of sustainable supply chain management practices. Additionally, the role of stakeholder pressure is frequently overlooked. Drawing on Natural Resources-Based View and Stakeholder Theory, this study aims to elucidate the ambiguous connection between sustainable supply management, sustainable process management, stakeholder pressure and performance, and investigate the mediation role of sustainable process management and the moderation effect of stakeholder pressure. Our analysis, based on data collected from 235 Chinese manufacturing firms, reveals significant insights. First, stakeholder pressure positively moderates the relationship between sustainable process management and performance, while negatively moderates the relationship between sustainable supply management and performance. Second, sustainable process management has a complete mediation effect on the relationship between sustainable supply management and performance. The conclusion not only explains the inconsistent relationship between sustainable supply chain management practice and performance, but also reveals clearly the relationship between sustainable supply management and sustainable process management. Besides, it also highlights the difference in performance outcomes of sustainable supply management and sustainable process management under stakeholder pressures, and has valuable guidance to the practice of sustainable supply chain management in Chinese manufacturing firms.
Management practices and manufacturing firm responses to a randomized energy audit
Increasing the efficiency of industrial energy use is widely considered important for mitigating climate change. We randomize assignment of an energy audit intervention aimed at improving energy efficiency and reducing energy expenditures of small- and medium-sized metal processing firms in Shandong Province, China, and examine impacts on energy outcomes and interactions with firms’ management practices. We find that the intervention reduced firms’ unit cost of electricity by 8% on average. Firms with more developed structured management practices showed higher rates of recommendation adoption. However, the post-intervention electricity unit cost reduction is larger in firms with less developed practices, primarily driven by a single recommendation that corrected managers’ inaccurate reporting of transformer usage at baseline, lowering their electricity costs. By closing management-associated gaps in awareness of energy expenditures, energy audit programmes may reduce a firm’s unit cost of energy but have an ambiguous impact on energy use and climate change.
An active representation learning method for reaction yield prediction with small-scale data
Reaction optimization plays an essential role in chemical research and industrial production. To explore a large reaction system, a practical issue is how to reduce the heavy experimental load for finding the high-yield conditions. In this paper, we present an efficient machine learning tool called “RS-Coreset”, where the key idea is to take advantage of deep representation learning techniques to guide an interactive procedure for representing the full reaction space. Our proposed tool only uses small-scale data, say 2.5% to 5% of the instances, to predict the yields of the reaction space. We validate the performance on three public datasets and achieve state-of-the-art results. Moreover, we apply this tool to assist the realistic exploration of the Lewis base-boryl radicals enabled dechlorinative coupling reactions in our lab. The tool can help us to effectively predict the yields and even discover several feasible reaction combinations that were overlooked in previous articles.
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