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This study focuses on China's electricity productivity post-pandemic, employing the Logarithmic Mean Divisia Index (LMDI) method and the Kaya identity. Despite the clarity of the electricity productivity indicator, factors like industrial structure, energy efficiency, and electrification rates contribute to fluctuations. Quantitative analysis reveals a decisive role of the terminal electrification rate in declining electricity productivity. The proposed analytical method provides a more accurate assessment of electricity's contribution to economic growth, aiding informed policy decisions for sustainable energy development in China.

With the large-scale access of renewable energy， the configuration of energy storage system （ESS） has become an important means to improve the flexibility and reliability of the grid. Given the problem of low utilization rate of ESS in a single-application scenario， an optimal configuration method of ESS for multi-application scenarios is proposed to improve the utilization rate of ESS and enhance the voltage stability of power grid. Firstly， this paper establishes a mathematical model of ESS under the three application scenarios of smoothing wind and solar output fluctuation， auxiliary frequency regulation and energy arbitrage； secondly， it takes account of the life attenuation caused by the cyclic charge and discharge of ESS and builds an optimization model of operation and scheduling to minimize the net cost of distribution networks， and further establishes a storage system configuration optimization model intending to minimize the total cost of energy storage system configuration； then， the optimal configuration model of energy storage is solved by combining genetic algorithm and GUROBI solver to obtain its optimal configuration scheme； finally， the proposed method is simulated and verified by IEEE 33 node system. The results show that the wind and PV generation output power and node voltage fluctuations in the distribution network are significantly reduced under multi-application scenarios； the operational stability of the grid is enhanced while the utilization of the energy storage is improved.

Aims/Introduction: To assess whether the sodium–glucose cotransporter 2 inhibitor, henagliflozin, improves cognitive impairment in patients with type 2 diabetes. Materials and Methods: We carried out a prospective study on 290 patients with type 2 diabetes and cognitive impairment. Montreal Cognitive Assessment scores and plasma phosphorylated tau181 levels were used to assess cognition. The association between henagliflozin use and changes in cognition was examined using multivariable logistic regression analysis. Results: Montreal Cognitive Assessment scores at enrollment and after 6 months were 21 (interquartile range [IQR]19–23) versus 22 (IQR 20–25; P < 0.0001) in all patients, 21 (IQR 19–23) versus 24 (IQR 22–26; P < 0.0001) in the henagliflozin group and 21 (IQR 19–22) versus 21 (IQR 19–23; P > 0.05) in the non‐sodium–glucose cotransporter 2 inhibitor group. Logistic regression analysis showed that henagliflozin treatment was associated with Montreal Cognitive Assessment score improvement independent of potential confounders (odds ratio [OR] 3.670, 95% confidence interval [CI] 2.224–6.056, P < 0.0001). Additionally, plasma phosphorylated tau181 levels significantly decreased at 6‐month follow up in all patients (OR 11.5, 95% CI 9.9–13.7 vs OR 10.1, 95% CI 7.8–12.9, P < 0.0001) and in the henagliflozin group (OR 11.5, 95% CI 10.3–13.0 vs OR 9.2, 95% CI 7.1–10.7, P < 0.0001), but not in the non‐sodium–glucose cotransporter 2 inhibitor group. Henagliflozin treatment was independently associated with decreased phosphorylated tau181 levels (OR 3.670, 95% CI 1.598–4.213, P < 0.0001). Conclusions: Henagliflozin treatment was independently associated with improvements in Montreal Cognitive Assessment scores and plasma phosphorylated tau181 levels, indicating significant beneficial effects on cognitive impairment in patients with type 2 diabetes. [ABSTRACT FROM AUTHOR]

A strong driving force for charge separation and transfer in semiconductors is essential for designing effective photoelectrodes for solar energy conversion. While defect engineering and polarization alignment can enhance this process, their potential interference within a photoelectrode remains unclear. Here we show that oxygen vacancies in bismuth vanadate (BiVO4) can create defect dipoles due to a disruption of symmetry. The modified photoelectrodes exhibit a strong correlation between charge separation and transfer capability and external electrical poling, which is not seen in unmodified samples. Applying poling at −150 Volt boosts charge separation and transfer efficiency to over 90%. A photocurrent density of 6.3 mA cm−2 is achieved on the photoelectrode after loading with a nickel-iron oxide-based cocatalyst. Furthermore, using generated holes for methane partial oxidation can produce methanol with a Faradaic efficiency of approximately 6%. These findings provide valuable insights into the photoelectrocatalytic conversion of greenhouse gases into valuable chemical products. The design of effective photoelectrodes for solar energy conversion relies on optimizing charge separation and transfer, which remain a challenge. In this study, the authors demonstrate that an external poling treatment can create a built-in electric field in bismuth vanadate photoelectrodes, thereby facilitating efficient charge transport for water oxidation and methane conversion. [ABSTRACT FROM AUTHOR]

This study introduces a novel architecture for value, preference, and boundary alignment in large language models (LLMs) and generative AI systems, accompanied by an experimental implementation. It addresses the limitations in AI model trustworthiness stemming from insufficient comprehension of personal context, preferences, and cultural diversity, which can lead to biases and safety risks. Using an inductive, qualitative research approach, we propose a framework for personalizing AI models to improve model alignment through additional context and boundaries set by users. Our framework incorporates user-friendly tools for identification, annotation, and simulation across diverse contexts, utilizing prompt-driven semantic segmentation and automatic labeling. It aims to streamline scenario generation and personalization processes while providing accessible annotation tools. The study examines various components of this framework, including user interfaces, underlying tools, and system mechanics. We present a pilot study that demonstrates the framework's ability to reduce the complexity of value elicitation and personalization in LLMs. Our experimental setup involves a prototype implementation of key framework modules, including a value elicitation interface and a fine-tuning mechanism for language models. The primary goal is to create a token-based system that allows users to easily impart their values and preferences to AI systems, enhancing model personalization and alignment. This research contributes to the democratization of AI model fine-tuning and dataset generation, advancing efforts in AI value alignment. By focusing on practical implementation and user interaction, our study bridges the gap between theoretical alignment approaches and real-world applications in AI systems. [ABSTRACT FROM AUTHOR]

Novel phase of nano materials that break the traditional structural constraints are highly desirable, particularly in the field of mechanocatalysis, offering versatile applications ranging from energy to medical diagnosis and treatment. In this work, a distinct layered barium dititanate (BaTi2O5) nanocrystals using a pH‐modulated hydrothermal method is successfully synthesized. These nanocrystals exhibit outstanding hydrogen generation capability (1160 µmol g−1 h−1 in pure water) and demonstrate remarkable performance in organic dye degradation using ultrasonication. The crystal structure of this newly discovered BaTi2O5 phase, is determined by a combination of synchrotron Powder Diffraction refinement and X‐ray adsorption techniques, including X‐ray Absorption Near Edge Structure (XANES) and Extended X‐ray Absorption Fine Structure (EXAFS). Density Functional Theory calculations revealed that the newly‐discovered BaTi2O5 phase demonstrates dipole moments along the z‐axis, distributed in an antiparallel direction within a single unit cell. These inherent dipoles induce a surface polarization and a ferroelectric‐flexoelectric response under mechanical stimuli when the materials go to nano dimension. With a band alignment well‐suitable for hydrogen and reactive oxygen species generation, this BaTi2O5 phase demonstrates promising potential for Mechanocatalysis. The discovery of this distinct phase not only enriches the material candidates for mechanocatalysis but also provides valuable insights. [ABSTRACT FROM AUTHOR]

Sugarcane smut caused by Sporisorium scitamineum represents the most destructive disease in the sugarcane industry, causing host hormone disruption and producing a black whip-like sorus in the apex of the stalk. In this study, the gibberellin metabolic pathway was found to respond to S. scitamineum infection, and the contents of bioactive gibberellins were significantly reduced in the leaves of diseased plants. The gibberellin receptor gene ScGID1 was identified and significantly downregulated. ScGID1 localized in both the nucleus and cytoplasm and had the highest expression level in the leaves. Eight proteins that interact with ScGID1 were screened out using a yeast two-hybrid assay. Novel DELLA proteins named ScGAI1a and ScGA20ox2, key enzymes in GA biosynthesis, were both found to interact with ScGID1 in a gibberellin-independent manner. Transcription factor trapping with a yeast one-hybrid system identified 50 proteins that interacted with the promoter of ScGID1, among which ScS1FA and ScPLATZ inhibited ScGID1 transcription, while ScGDSL promoted transcription. Overexpression of ScGID1 in transgenic Nicotiana benthamiana plants could increase plant height and promote flowering. These results not only contribute to improving our understanding of the metabolic regulatory network of sugarcane gibberellin but also expand our knowledge of the interaction between sugarcane and pathogens. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore the heterogeneity of tumor endothelial cells (TECs) in hepatocellular carcinoma (HCC) and their role in tumor progression, with the goal of identifying new therapeutic targets and strategies to improve patient prognosis. Methods: Single-cell RNA sequencing data from nine primary liver cancer samples were analyzed, obtained from the Gene Expression Omnibus (GEO) database. Data preprocessing, normalization, dimensionality reduction, and batch effect correction were performed based on the Seurat package. HCC cell types were identified using uniform manifold approximation and projection (UMAP) and cluster analysis, and the different cell types were annotated using the CellMarker database. Pseudotime trajectory analysis was conducted with Monocle to explore the differentiation trajectory of TECs. MAPK signaling pathway activity and copy number variations (CNV) in TECs were analyzed in conjunction with data from The Cancer Genome Atlas (TCGA), the trans-well and wound healing assay was used for cell invasion and migration activity assessment. Results: Two subgroups of TECs (TECs 1 and TECs 2) were identified, exhibiting distinct functional activities and signaling pathways. Specifically, TECs 1 may be involved in tumor cell proliferation and inflammatory responses, whereas TECs 2 is not only involved in cell proliferation pathways, but also enriched in pathways such as metabolic synthesis. Pseudotime analysis revealed dynamic changes in TECs subgroups during HCC progression, correlating specific gene expressions (such as PDGFRB, PGF, JUN, and NR4A1). Subsequently, the JUN gene was predicted by performing binding sites and was shown to act as a transcription factor that may regulate the expression of the PGF gene. CNV analysis highlighted key genes and pathways in TECs that might influence HCC progression, and the PGF as key regulatory factor mediated cell proliferation and migration. Conclusion: The study revealed the heterogeneity of TECs in HCC and their potential roles in tumor progression, offering new perspectives and potential therapeutic targets for HCC molecular mechanisms. The findings emphasize the importance of further exploring TECs heterogeneity for understanding HCC pathogenesis and developing personalized treatment strategies. [ABSTRACT FROM AUTHOR]

Simple Summary: Fourier Transform Infrared Spectroscopy (FT-MIRS) is widely used in milk quality detection, dairy herd improvement (DHI), and other fields. It is an economical, fast, accurate, and nondestructive batch tool for determining production performance phenotypes of dairy cows. Milk is one of the most important ways to provide the human body with the fatty acids it needs. There are a huge number of dairy cows in China. Therefore, it is possible to control fatty acid production in the milk source through targeted husbandry and breeding on large pastures to improve the quality of milk production. However, this work has not yet officially begun in China. In summary, our work uses FT-MIRS for the first time to study the phenotypic properties of milk fatty acid content and the genetic mechanism of its formation and to estimate genetic parameters. At the same time, SNPs significantly related to fatty acid content were discovered and the genes or adjacent genes had critical regulatory effects on milk fat synthesis, milk protein synthesis, adipocyte differentiation, mammary gland development, milk synthesis, and growth and development in dairy cows, thus providing a new perspective for cow genetic selection in China. Fourier Transform Mid-Infrared Spectroscopy (FT-MIRS) can be used for quantitative detection of milk components. Here, milk samples of 458 Chinese Holstein cows from 11 provinces in China were collected and we established a total of 22 quantitative prediction models in milk fatty acids by FT-MIRS. The coefficient of determination of the validation set ranged from 0.59 (C18:0) to 0.76 (C4:0). The models were adopted to predict the milk fatty acids from 2138 cows and a new high-throughput computing software HiBLUP was employed to construct a multi-trait model to estimate and analyze genetic parameters in dairy cows. Finally, genome-wide association analysis was performed and seven novel SNPs significantly associated with fatty acid content were selected, investigated, and verified with the FarmCPU method, which stands for "Fixed and random model Circulating Probability Unification". The findings of this study lay a foundation and offer technical support for the study of fatty acid trait breeding and the screening and grouping of characteristic dairy cows in China with rich, high-quality fatty acids. It is hoped that in the future, the method established in this study will be able to screen milk sources rich in high-quality fatty acids. [ABSTRACT FROM AUTHOR]

Simple Summary: Various studies have confirmed that the parity, days in milk (DIM), and somatic cell score (SCS) affected the fatty acid contents in milk and the Fourier-transform mid-infrared spectroscopy (FT-MIRS). However, the characteristics of fatty acid group contents predicted by FT-MIRS in Chinese Holstein cows have not been clearly demonstrated. This study employed FT-MIRS data to study the influencing factors and alterations in milk fatty acid contents in Chinese Holstein cows from large-scale dairy farms in Northern China. This study provided new ideas for the expansion of Dairy Herd Improvement laboratory determination indicators in China and the breeding of dairy cows with excellent milk quality. Fatty acid is an important factor affecting the nutritional quality of milk. In this study, we collected and assessed 78,086 milk samples from 12,065 Chinese Holstein cows from 11 farms in Northern China from November 2019 to September 2022. The contents of eight fatty acid groups were predicted using FT-MIRS-based models. The contents of TFAs, SFAs, UFAs, MUFAs, PUFAs, and LCFAs in milk reached the highest at 96–125 DIM, and SCFA and MCFA contents reached the highest at 276–305 DIM. With the increase in somatic cell score, the contents of various fatty acid groups in milk gradually decreased, and the nutritional value of milk and flavor of dairy products gradually deteriorated. The contents of high-quality fatty acids in milk, particularly UFAs and MUFAs, were significantly higher in the non-pregnant state than in the pregnant state. However, SCFA and MCFA contents exhibited the opposite pattern. Our findings provided valuable information on the content and distribution range of fatty acid groups in milk from Chinese Holstein cows. Further analysis is warranted to explore the breeding of Chinese Holstein cows providing milk with abundant beneficial fatty acids. [ABSTRACT FROM AUTHOR]

5-Fluorouracil (5-FU) is widely used in the treatment of gastric cancer, and the emergence of drug resistance and toxic effects has limited its application. Therefore, there is an urgent need for safe and effective novel drugs or new therapies. β-Ionone (BI) is found in vegetables and fruits and possesses an inhibitory proliferation of tumor cells in vitro and in vivo. In this study, we investigated whether BI could enhance the inhibitory effects of 5-FU on the proliferation of gastric adenocarcinoma cells and the growth of gastric cancer cell xenografts in a mouse model. The effects of BI and 5-FU alone or their combination on the cell viability, apoptosis, and mitochondrial membrane potential, the cell cycle, and its related proteins—Cyclin D1, and CDK4 as well as PCNA and GSK-3β were evaluated in SGC-7901 cells and MKN45 cells by MTT, MB, flow cytometry and Western blot. In addition, the effects of BI and 5-FU alone or their combination on the growth of SGC-7901 cell xenografts in nude mice were investigated. The results showed that BI significantly enhanced the sensitivity of gastric adenocarcinoma cells to 5-FU in vitro and in vivo, i.e. proliferation inhibited, apoptosis induced and GSK-3β protein activated. Therefore, our results suggest that BI increases the antitumor effect of 5-FU on gastric adenocarcinoma cells, at least partly from an activated GSK-3β signaling pathway. [ABSTRACT FROM AUTHOR]