Integrated transcriptomic and metabolomic data reveal the cold stress responses molecular mechanisms of two coconut varieties.

Among tropical fruit trees, coconut holds significant edible and economic importance. The natural growth of coconuts faces a challenge in the form of low temperatures, which is a crucial factor among adverse environmental stresses impacting their geographical distribution. Hence, it is essential to enhance our comprehension of the molecular mechanisms through which cold stress influences various coconut varieties. We employed analyses of leaf growth morphology and physiological traits to examine how coconuts respond to low temperatures over 2-hour, 8-hour, 2-day, and 7-day intervals. Additionally, we performed transcriptome and metabolome analyses to identify the molecular and physiological shifts in two coconut varieties displaying distinct sensitivities to the cold stress. As the length of cold stress extended, there was a prominent escalation within the soluble protein (SP), proline (Pro) concentrations, the activity of peroxidase (POD) and superoxide dismutase (SOD) in the leaves. Contrariwise, the activity of glutathione peroxidase (GSH) underwent a substantial reduction during this period. The widespread analysis of metabolome and transcriptome disclosed a nexus of genes and metabolites intricately cold stress were chiefly involved in pathways centered around amino acid, flavonoid, carbohydrate and lipid metabolism. We perceived several stress-responsive metabolites, such as flavonoids, carbohydrates, lipids, and amino acids, which unveiled considerably, lower in the genotype subtle to cold stress. Furthermore, we uncovered pivotal genes in the amino acid biosynthesis, antioxidant system and flavonoid biosynthesis pathway that presented down-regulation in coconut varieties sensitive to cold stress. This study broadly enriches our contemporary perception of the molecular machinery that contributes to altering levels of cold stress tolerance amid coconut genotypes. It also unlocks several unique prospects for exploration in the areas of breeding or engineering, aiming to identifying tolerant and/or sensitive coconut varieties encompassing multi-omics layers in response to cold stress conditions.

The application of large language models in medicine: A scoping review.

This study systematically reviewed the application of large language models (LLMs) in medicine, analyzing 550 selected studies from a vast literature search. LLMs like ChatGPT transformed healthcare by enhancing diagnostics, medical writing, education, and project management. They assisted in drafting medical documents, creating training simulations, and streamlining research processes. Despite their growing utility in assisted diagnosis and improving doctor-patient communication, challenges persisted, including limitations in contextual understanding and the risk of over-reliance. The surge in LLM-related research indicated a focus on medical writing, diagnostics, and patient communication, but highlighted the need for careful integration, considering validation, ethical concerns, and the balance with traditional medical practice. Future research directions suggested a focus on multimodal LLMs, deeper algorithmic understanding, and ensuring responsible, effective use in healthcare.

Integrated transcriptomics and metabolomics analyses of the effects of bagging treatment on carotenoid biosynthesis and regulation of Areca catechu L.

Introduction: Fresh Aareca nut fruit for fresh fruit chewing commonly found in green or dark green hues. Despite its economic significance, there is currently insufficient research on the study of color and luster of areca. And the areca nut fruits after bagging showed obvious color change from green to tender yellow. In the study, we tried to explain this interesting variation in exocarp color. Methods: Fruits were bagged (with a double-layered black interior and yellow exterior) 45 days after pollination and subsequently harvested 120 days after pollination. In this study, we examined the the chlorophyll and carotenoid content of pericarp exocarp, integrated transcriptomics and metabolomics to study the effects of bagging on the carotenoid pathway at the molecular level. Results: It was found that the chlorophyll and carotenoid content of bagged areca nut (YP) exocarp was significantly reduced. A total of 21 differentially expressed metabolites (DEMs) and 1784 differentially expressed genes (DEGs) were screened by transcriptomics and metabolomics. Three key genes in the carotenoid biosynthesis pathway as candidate genes for qPCR validation by co-analysis, which suggested their role in the regulation of pathways related to crtB, crtZ and CYP707A. Discussion: We described that light intensity may appear as a main factor influencing the noted shift from green to yellow and the ensuing reduction in carotenoid content after bagging.

ASP: Learn a Universal Neural Solver!

Applying machine learning to combinatorial optimization problems has the potential to improve both efficiency and accuracy. However, existing learning-based solvers often struggle with generalization when faced with changes in problem distributions and scales. In this paper, we propose a new approach called ASP: Adaptive Staircase Policy Space Response Oracle to address these generalization issues and learn a universal neural solver. ASP consists of two components: Distributional Exploration, which enhances the solver's ability to handle unknown distributions using Policy Space Response Oracles, and Persistent Scale Adaption, which improves scalability through curriculum learning. We have tested ASP on several challenging COPs, including the traveling salesman problem, the vehicle routing problem, and the prize collecting TSP, as well as the real-world instances from TSPLib and CVRPLib. Our results show that even with the same model size and weak training signal, ASP can help neural solvers explore and adapt to unseen distributions and varying scales, achieving superior performance. In particular, compared with the same neural solvers under a standard training pipeline, ASP produces a remarkable decrease in terms of the optimality gap with 90.9% and 47.43% on generated instances and real-world instances for TSP, and a decrease of 19% and 45.57% for CVRP.

Combined transcriptome and metabolome analysis of sugar and fatty acid of aromatic coconut and non-aromatic coconut in China.

Sugar and fatty acid content are among the important factors that contribute to the intensity of flavor in aromatic coconut. Gaining a comprehensive understanding of the sugar and fatty acid metabolites in the flesh of aromatic coconuts, along with identifying the key synthetic genes, is of significant importance for improving the development of desirable character traits in these coconuts. However, the related conjoint analysis of metabolic targets and molecular synthesis mechanisms has not been carried out in aromatic coconut until now. UPLC-MS/MS combined with RNA-Seq were performed in aromatic coconut (AC) and non-aromatic coconut (NAC) meat at 7, 9 and 11 months. The results showed that D-fructose in AC coconut meat was 3.48, 2.56 and 3.45 fold higher than that in NAC coconut meat. Similarly, D-glucose in AC coconut meat was 2.48, 2.25 and 3.91 fold higher than that in NAC coconut meat. The NAC coconut meat showed a 1.22-fold rise in the content of lauric acid compared to the AC coconut meat when it reached 11 months of age. Myristic acid content in NAC coconut meat was 1.47, 1.44 and 1.13 fold higher than that in AC coconut meat. The palmitic acid content in NAC coconut meat was 1.62 and 1.34 fold higher than that in AC coconut meat. The genes SPS, GAE, GALE, GLCAK, UGE, UGDH, FBP, GMLS, PFK, GPI, RHM, ACC, FabF, FatA, FabG, and FabI exhibited a negative correlation with D-fructose (r = -0.81) and D-glucose (r = -0.99) contents, while showing a positive correlation (r = 0.85-0.96) with lauric acid and myristic acid. Furthermore, GALE, GLCAK, FBP, GMLS, and ACC displayed a positive correlation (r = 0.83-0.94) with palmitic acid content. The sugar/organic acid ratio exhibited a positive correlation with SPS, GAE, UGE, FabF, FabZ and FabI.

Bi-DexHands: Towards Human-Level Bimanual Dexterous Manipulation.

Achieving human-level dexterity in robotics remains a critical open problem. Even simple dexterous manipulation tasks pose significant difficulties due to the high number of degrees of freedom and the need for cooperation among heterogeneous agents (e.g., finger joints). While some researchers have utilized reinforcement learning (RL) to control a single hand in manipulating objects, tasks that require coordinated bimanual cooperation are still under-explored due to the fewer suitable environments, which can result in difficulties and sub-optimal performance. To address these challenges, we introduce Bi-DexHands, a simulator with two dexterous hands featuring 20 bimanual manipulation tasks and thousands of target objects, designed to match various levels of human motor skills based on cognitive science research. We developed Bi-DexHands in Issac Gym, enabling highly efficient RL training at over 30,000 frames per second using a single NVIDIA RTX 3090. Based on Bi-DexHands, we present a comprehensive evaluation of popular RL algorithms in different settings, including single-agent/multi-agent RL, offline RL, multi-task RL, and meta RL. Our findings show that on-policy algorithms, such as PPO, can master simple manipulation tasks that correspond to those of 48-month-old babies, such as catching a flying object or opening a bottle. Furthermore, multi-agent RL can improve the ability to perform manipulations that require skilled bimanual cooperation, such as lifting a pot or stacking blocks. Despite achieving success in individual tasks, current RL algorithms struggle to learn multiple manipulation skills in most multi-task and few-shot learning scenarios. This highlights the need for further research and development within the RL community.

Widely targeted metabolomics combined with E-tongue and E-nose reveal dynamic changes of tender coconut water in responses to the infection of Ceratocystis paradoxa.

Ceratocystis paradoxa is a major cause of postharvest disease in tender coconuts worldwide. We conducted a comprehensive study using widely targeted metabolomics, electronic tongue (E-tongue), and electronic nose (E-nose) analyses to investigate the impacts of C. paradoxa invasion on the quality of tender coconut water (TCW) from fresh control (FC), uninoculated (UN), skin-inoculated (SI), and deep-inoculated (DI) nuts. DI exhibited significantly higher taste indicators associated with bitterness, saltiness, astringency aftertaste, and bitter aftertaste, as well as odor sensor values related to various compounds such as long-chain alkanes, hydrides, methane, organic sulfides, etc. Invasion of C. paradoxa into the endosperm altered the flavor characteristics of TCW mainly through the modulation of carbohydrate and secondary metabolite pathways. Furthermore, significant correlations were observed between the differentially expressed flavorful metabolites and the sensor indicators of the E-nose and E-tongue. These findings offer valuable insights into understanding the impact of C. paradoxa infection on coconuts.

Integrated Transcriptomic and Metabolomics Analyses Reveal Molecular Responses to Cold Stress in Coconut (Cocos nucifera L.) Seedlings.

Coconut is an important tropical and subtropical fruit and oil crop severely affected by cold temperature, limiting its distribution and application. Thus, studying its low-temperature reaction mechanism is required to expand its cultivation range. We used growth morphology and physiological analyses to characterize the response of coconuts to 10, 20, and 30 d of low temperatures, combined with transcriptome and metabolome analysis. Low-temperature treatment significantly reduced the plant height and dry weight of coconut seedlings. The contents of soil and plant analyzer development (SPAD), soluble sugar (SS), soluble protein (SP), proline (Pro), and malondialdehyde (MDA) in leaves were significantly increased, along with the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), and the endogenous hormones abscisic acid (ABA), auxin (IAA), zeatin (ZR), and gibberellin (GA) contents. A large number of differentially expressed genes (DEGs) (9968) were detected under low-temperature conditions. Most DEGs were involved in mitogen-activated protein kinase (MAPK) signaling pathway-plant, plant hormone signal transduction, plant-pathogen interaction, biosynthesis of amino acids, amino sugar and nucleotide sugar metabolism, carbon metabolism, starch and sucrose metabolism, purine metabolism, and phenylpropanoid biosynthesis pathways. Transcription factors (TFs), including WRKY, AP2/ERF, HSF, bZIP, MYB, and bHLH families, were induced to significantly differentially express under cold stress. In addition, most genes associated with major cold-tolerance pathways, such as the ICE-CBF-COR, MAPK signaling, and endogenous hormones and their signaling pathways, were significantly up-regulated. Under low temperatures, a total of 205 differentially accumulated metabolites (DAMs) were enriched; 206 DAMs were in positive-ion mode and 97 in negative-ion mode, mainly including phenylpropanoids and polyketides, lipids and lipid-like molecules, benzenoids, organoheterocyclic compounds, organic oxygen compounds, organic acids and derivatives, nucleosides, nucleotides, and analogues. Comprehensive metabolome and transcriptome analysis revealed that the related genes and metabolites were mainly enriched in amino acid, flavonoid, carbohydrate, lipid, and nucleotide metabolism pathways under cold stress. Together, the results of this study provide important insights into the response of coconuts to cold stress, which will reveal the underlying molecular mechanisms and help in coconut screening and breeding.

Utilizing Dichloromethane as an Extremely Proficient Substitute for Phenol/Chloroform in Extracting RNA with Exceptional Purity from Woody Tissues of Coconut.

Procuring high-grade RNA from mature coconut tissues is a tricky and labor-intensive process due to the intricate scaffold of polysaccharides, polyphenols, lipids, and proteins that form firm complexes with nucleic acids. However, we have effectively developed a novel method for the first time, letting the retrieval of high-grade RNA from the roots, endosperm, and mesocarp of mature coconut trees take place. In this method, we exploited dichloromethane as a replacement to phenol/chloroform for RNA recovery from mature coconut tissues. The amount of high-grade RNA acquired from the roots of mature coconut trees was 120.7 µg/g, with an A260/280 ratio of 1.95. Similarly, the mature coconut mesocarp yielded 134.6 µg/g FW of quality RNA with A260/280 ratio of 1.98, whereas the mature coconut endosperm produced 120.4 µg/g FW of quality RNA with A260/280 ratio of 2.01. Furthermore, the RNA isolation using the dichloromethane method exhibited excellent performance in downstream experiments, particularly in RT-PCR for cDNA production and amplification. On the contrary, the RNA plant kit, TRIZOL, and Cetyl Trimethyl Ammonium Bromide (CTAB) methods were unsuccessful in isolating substantial quantities of RNA with exceptional purities from the mentioned coconut tissues. In view of these findings, we conclude that the newly developed method will be pivotal in effectively extracting RNA with high purity from mature coconut tissues.

Parameter Optimization for Printing Barium Titanate Piezoelectric Ceramics through Digital Light Processing.

Digital light processing (DLP) technology has emerged as a promising 3D printing technology with the potential for the efficient manufacturing of complex ceramic devices. However, the quality of printed products is highly dependent on various process parameters, including slurry formulation, heat treatment process, and poling process. This paper optimizes the printing process with respect to these key parameters, such as using a ceramic slurry with 75 wt% powder content. The employed degreasing heating rate is 4 °C/min, the carbon-removing heating rate is 4 °C/min, and the sintering heating rate is 2 °C/min for heat treatment of the printed green body. The resulting parts are polarized using a poling field of 10 kV/cm, a poling time of 50 min, and a poling temperature of 60 °C, which yields a piezoelectric device with a high piezoelectric constant of 211 pC/N. To demonstrate the practical application of the device, its use as a force sensor and magnetic sensor is validated.

Effect of Strontium Substitution on the Tribocatalytic Performance of Barium Titanate.

This study investigates the impact of Sr doping on the tribocatalytic performance of BaTiO3 in degrading organic pollutants. Ba1-xSrxTiO3 (x = 0-0.3) nanopowders are synthesized and their tribocatalytic performance evaluated. By doping Sr into BaTiO3, the tribocatalytic performance was enhanced, resulting in an approximately 35% improvement in the degradation efficiency of Rhodamine B using Ba0.8Sr0.2TiO3. Factors such as the friction contact area, stirring speed, and materials of the friction pairs also influenced the dye degradation. Electrochemical impedance spectroscopy revealed that Sr doping improved BaTiO3's charge transfer efficiency, thereby boosting its tribocatalytic performance. These findings indicate potential applications for Ba1-xSrxTiO3 in dye degradation processes.

Integrated transcriptomic and metabolomic analyses reveal key metabolic pathways in response to potassium deficiency in coconut (Cocos nucifera L.) seedlings.

Potassium ions (K+) are important for plant growth and crop yield. However, the effects of K+ deficiency on the biomass of coconut seedlings and the mechanism by which K+ deficiency regulates plant growth remain largely unknown. Therefore, in this study, we compared the physiological, transcriptome, and metabolite profiles of coconut seedling leaves under K+-deficient and K+-sufficient conditions using pot hydroponic experiments, RNA-sequencing, and metabolomics technologies. K+ deficiency stress significantly reduced the plant height, biomass, and soil and plant analyzer development value, as well as K content, soluble protein, crude fat, and soluble sugar contents of coconut seedlings. Under K+ deficiency, the leaf malondialdehyde content of coconut seedlings were significantly increased, whereas the proline (Pro) content was significantly reduced. Superoxide dismutase, peroxidase, and catalase activities were significantly reduced. The contents of endogenous hormones such as auxin, gibberellin, and zeatin were significantly decreased, whereas abscisic acid content was significantly increased. RNA-sequencing revealed that compared to the control, there were 1003 differentially expressed genes (DEGs) in the leaves of coconut seedlings under K+ deficiency. Gene Ontology analysis revealed that these DEGs were mainly related to "integral component of membrane," "plasma membrane," "nucleus", "transcription factor activity," "sequence-specific DNA binding," and "protein kinase activity." Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that the DEGs were mainly involved in "MAPK signaling pathway-plant," "plant hormone signal transduction," "starch and sucrose metabolism," "plant-pathogen interaction," "ABC transporters," and "glycerophospholipid metabolism." Metabolomic analysis showed that metabolites related to fatty acids, lipidol, amines, organic acids, amino acids, and flavonoids were generally down-regulated in coconut seedlings under K+ deficiency, whereas metabolites related to phenolic acids, nucleic acids, sugars, and alkaloids were mostly up-regulated. Therefore, coconut seedlings respond to K+ deficiency stress by regulating signal transduction pathways, primary and secondary metabolism, and plant-pathogen interaction. These results confirm the importance of K+ for coconut production, and provide a more in-depth understanding of the response of coconut seedlings to K+ deficiency and a basis for improving K+ utilization efficiency in coconut trees.

Corrigendum to On the complexity of computing Markov perfect equilibrium in general-sum stochastic games.

[This corrects the article DOI: 10.1093/nsr/nwac256.].

On the complexity of computing Markov perfect equilibrium in general-sum stochastic games.

Similar to the role of Markov decision processes in reinforcement learning, Markov games (also called stochastic games) lay down the foundation for the study of multi-agent reinforcement learning and sequential agent interactions. We introduce approximate Markov perfect equilibrium as a solution to the computational problem of finite-state stochastic games repeated in the infinite horizon and prove its PPAD-completeness. This solution concept preserves the Markov perfect property and opens up the possibility for the success of multi-agent reinforcement learning algorithms on static two-player games to be extended to multi-agent dynamic games, expanding the reign of the PPAD-complete class.

Improved stacking ensemble learning based on feature selection to accurately predict warfarin dose.

Background: With the rapid development of artificial intelligence, prediction of warfarin dose via machine learning has received more and more attention. Since the dose prediction involve both linear and nonlinear problems, traditional machine learning algorithms are ineffective to solve such problems at one time. Objective: Based on the characteristics of clinical data of Chinese warfarin patients, an improved stacking ensemble learning can achieve higher prediction accuracy. Methods: Information of 641 patients from southern China who had reached a steady state on warfarin was collected, including demographic information, medical history, genotype, and co-medication status. The dataset was randomly divided into a training set (90%) and a test set (10%). The predictive capability is evaluated on a new test set generated by stacking ensemble learning. Additional factors associated with warfarin dose were discovered by feature selection methods. Results: A newly proposed heuristic-stacking ensemble learning performs better than traditional-stacking ensemble learning in key metrics such as accuracy of ideal dose (73.44%, 71.88%), mean absolute errors (0.11 mg/day, 0.13 mg/day), root mean square errors (0.18 mg/day, 0.20 mg/day) and R2 (0.87, 0.82). Conclusions: The developed heuristic-stacking ensemble learning can satisfactorily predict warfarin dose with high accuracy. A relationship between hypertension, a history of severe preoperative embolism, and warfarin dose is found, which provides a useful reference for the warfarin dose administration in the future.

Genome-wide identification, classification and expression analysis of MYB gene family in coconut (Cocos nucifera L.).

MYB transcription factors regulate the growth, development, and secondary metabolism of plant species. To investigate the origin of color variations in coconut pericarp, we identified and analyzed the MYB gene family present in coconut. According to the sequence of MYB genes in Arabidopsis thaliana, homologous MYB gene sequences were found in the whole genome database of coconut, the conserved sequence motifs within MYB proteins were analyzed by Motif Elicitation (MEME) tool, and the sequences without conservative structure were eliminated. Additionally, we employed RNA-seq technology to generate gene expression signatures of the R2R3-MYB genes across distinctive coconut parts exhibiting diverse colors. To validate these profiles, we conducted quantitative PCR (qPCR). Through comprehensive genome-wide screening, we successfully identified a collection of 179 MYB genes in coconut. Subsequent phylogenetic analysis categorized these 179 coconut MYB genes into 4-subfamilies: 124 R2R3-MYB, 4 3R-MYB types, 4 4R-MYB type, and 47 unknown types. Furthermore, these genes were further divided into 34 subgroups, with 28 of these subgroups successfully classified into known subfamilies found in Arabidopsis thaliana. By mapping the CnMYB genes onto the 16 chromosomes of the coconut genome, we unveiled a collinearity association between them. Moreover, a preservation of gene structure and motif distribution was observed across the CnMYB genes. Our research encompassed a thorough investigation of the R2R3-MYB genes present in the coconut genome, including the chromosomal localization, gene assembly, conserved regions, phylogenetic associations, and promoter cis-acting elements of the studied genes. Our findings revealed a collection of 12 R2R3-MYB candidate genes, namely CnMYB8, CnMYB15, CnMYB27, CnMYB28, CnMYB61, CnMYB63, CnMYB68, CnMYB94, CnMYB101, CnMYB150, CnMYB153, and CnMYB164. These genes showed differential expressions in diverse tissues and developmental stages of four coconut species, such as CnMYB68, CnMYB101, and CnMYB28 exhibited high expression in majority of tissues and coconut species, while CnMYB94 and CnMYB164 showed lower expression. These findings shed light on the crucial functional divergence of CnMYB genes across various coconut tissues, suggesting these genes as promising candidate genes for facilitating color development in this important crop.

Integrative Omics Analysis of Three Oil Palm Varieties Reveals (Tanzania × Ekona) TE as a Cold-Resistant Variety in Response to Low-Temperature Stress.

Oil palm (Elaeis guineensis Jacq.) is an economically important tropical oil crop widely cultivated in tropical zones worldwide. Being a tropical crop, low-temperature stress adversely affects the oil palm. However, integrative leaf transcriptomic and proteomic analyses have not yet been conducted on an oil palm crop under cold stress. In this study, integrative omics transcriptomic and iTRAQ-based proteomic approaches were employed for three oil palm varieties, i.e., B × E (Bamenda × Ekona), O × G (E. oleifera × Elaeis guineensis), and T × E (Tanzania × Ekona), in response to low-temperature stress. In response to low-temperature stress at (8 °C) for 5 days, a total of 5175 up- and 2941 downregulated DEGs in BE-0_VS_BE-5, and a total of 3468 up- and 2443 downregulated DEGs for OG-0_VS_OG-5, and 3667 up- and 2151 downregulated DEGs for TE-0_VS_TE-5 were identified. iTRAQ-based proteomic analysis showed 349 up- and 657 downregulated DEPs for BE-0_VS_BE-5, 372 up- and 264 downregulated DEPs for OG-0_VS_OG-5, and 500 up- and 321 downregulated DEPs for TE-0_VS_TE-5 compared to control samples treated at 28 °C and 8 °C, respectively. The KEGG pathway correlation of oil palm has shown that the metabolic synthesis and biosynthesis of secondary metabolites pathways were significantly enriched in the transcriptome and proteome of the oil palm varieties. The correlation expression pattern revealed that TE-0_VS_TE-5 is highly expressed and BE-0_VS_BE-5 is suppressed in both the transcriptome and proteome in response to low temperature. Furthermore, numerous transcription factors (TFs) were found that may regulate cold acclimation in three oil palm varieties at low temperatures. Moreover, this study identified proteins involved in stresses (abiotic, biotic, oxidative, and heat shock), photosynthesis, and respiration in iTRAQ-based proteomic analysis of three oil palm varieties. The increased abundance of stress-responsive proteins and decreased abundance of photosynthesis-related proteins suggest that the TE variety may become cold-resistant in response to low-temperature stress. This study may provide a basis for understanding the molecular mechanism for the adaptation of oil palm varieties in response to low-temperature stress in China.

Genome-Wide Identification of the DOF Gene Family Involved in Fruitlet Abscission in Areca catechu L.

Fruitlet abscission frequently occurs in Areca catechu L. and causes considerable production loss. However, the inducement mechanism of fruitlet abscission remains mysterious. In this study, we observed that the cell architecture in the abscission zone (AZ) was distinct with surrounding tissues, and varied obviously before and after abscission. Transcriptome analysis of the "about-to-abscise" and "non-abscised" AZs were performed in A. catechu, and the genes encoding the plant-specific DOF (DNA-binding with one finger) transcription factors showed a uniform up-regulation in AZ, suggesting a role of the DOF transcription in A. catechu fruitlet abscission. In total, 36 members of the DOF gene family distributed in 13 chromosomes were identified from the A. catechu genome. The 36 AcDOF genes were classified into nine subgroups based on phylogenic analysis. Six of them showed an AZ-specific expression pattern, and their expression levels varied according to the abscission process. In total, nine types of phytohormone response cis-elements and five types of abiotic stress related cis-elements were identified in the promoter regions of the AcDOF genes. In addition, histochemical staining showed that lignin accumulation of vascular bundles in AZ was significantly lower than that in pedicel and mesocarp, indicating the specific characteristics of the cell architecture in AZ. Our data suggests that the DOF transcription factors might play a role in fruitlet abscission regulation in A. catechu.

Illiquidity Comovement and Market Crisis.

This paper presents a rational expectation equilibrium model to explore how the financial contagion occurs between the unlinked markets that do not share common fundamentals. In the proposed model, the authors assume two of the three risky assets share no common fundamental factors, but are connected by one intermediate asset via cross fundamentals. Through this channel, investors transmit fundamental risk from one asset to another by dint of the cross fundamentals. This mechanism causes liquidity comovement and subsequently becomes a source of market crisis: Through the contagion mechanism, an initial liquidity shock in one asset can result in a drop tendency in liquidity and price informativeness for another asset. Such comovement in liquidity offers a new explanation for idiosyncratic assets in financial contagion.

Enhancing Comprehensive Energy Storage Properties in Tungsten Bronze Sr0.53Ba0.47Nb2O6-Based Lead-free Ceramics by B-Site Doping and Relaxor Tuning.

Dielectric ceramics with relaxor characteristics are promising candidates to meet the demand for capacitors of next-generation pulse devices. Herein, a lead-free Sb-modified (Sr0.515Ba0.47Gd0.01) (Nb1.9-xTa0.1Sbx)O6 (SBGNT-based) tungsten bronze ceramic is designed and fabricated for high-density energy storage capacitors. Using a B-site engineering strategy to enhance the relaxor characteristics, Sb incorporation could induce the structural distortion of the polar unit BO6 and order-disorder distribution of B-site cations as well as the modulation of polarization in the SBGNT-based tungsten bronze ceramic. More importantly, benefiting from the effective inhibition of abnormal growth of non-equiaxed grains, Sb introduction into SBGNT-based ceramics could effectively suppress the conductivity and leakage current density, enhancing the breakdown strength, as proved by the electrical impedance spectra. Consequently, a remarkable comprehensive performance via balancing recoverable energy density (∼3.26 J/cm3) and efficiency (91.95%) is realized simultaneously at 380 kV/cm, which surpasses that of the pristine sample without the Sb dopant (2.75 J/cm3 and 80.5%, respectively). The corresponding ceramics display superior stability in terms of fatigue (105 cycles), frequency (1∼200 Hz), and temperature (20∼140 °C). Further charge-discharge analysis indicates that a high power density (89.57 MW/cm3) and an impressive current density (1194.27 A/cm2) at 150 kV/cm are achieved simultaneously. All of the results demonstrate that the tungsten bronze relaxors are indeed gratifying lead-free candidate materials for dielectric energy storage applications.