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Utilizing the European Centre for Medium-Range Weather Forecast (ECMWF) Reanalysis v5 (ERA5), for the first time, we have confirmed close links among Sudden Stratospheric Warmings (SSWs) in the Northern Hemisphere (NH), the polar vortices, and stratospheric Planetary Waves (PWs) by analyzing and comparing their trends. Interestingly, within overall increasing trends, the duration and strength of SSWs exhibit increasing and decreasing trends before and after the winter of 2002, respectively. To reveal possible physical mechanisms driving these trends, we analyzed the long-term trends of the winter (from December to February) polar vortices and of stratospheric PWs with zonal wave number 1. Notably, our results show that in all three time periods (the entire period of 41 winters, 1980 to 2020, and the two subperiods — 1980−2002 and 2002−2020) enhancing SSWs were always accompanied by weakening winter polar vortices and strengthening polar PWs like Stationary Planetary Waves (SPWs) and 16-day waves, and vice versa. This is the first proof, based on ERA5 long-term trend data, that weakening polar vortices and enhancing stratospheric PWs (especially SPWs) could cause an increase in SSWs.

The increasing demand for high-strength lightweight hollow shafts in transportation highlights the need for advanced fabrication techniques. Al–Zn–Mg–Cu alloys, noted for their superior properties, are selected for three-roll skew rolling (TRSR). In TRSR, the material undergoes combined axial tensile and radial compressive stresses. This study evaluates the feasibility of TRSR for producing high-strength lightweight hollow stepped shafts from Al–Zn–Mg–Cu alloy. An integrated approach, including constitutive modeling, hot processing map development, and TRSR numerical simulations/experiments, is employed to optimize the TRSR forming process. The constitutive model was established based on 300°C–450 °C & 0.01–10 s−1 hot compression and 350°C–430 °C & 0.1–5 s−1 high-temperature tensile test data. The established Johnson-Cook optimization by genetic algorithms (GA-JC) model and unified viscoplastic constitutive model, accurately capture the alloy's hot deformation behavior, exhibiting minimal average absolute relative errors (AARE) of 5.431% and 5.808%, respectively. Microstructure evolution analyses shed light on the predominant softening mechanisms, emphasizing dynamic recovery (DRV) at elevated strain rates and diminishing texture intensity with escalating deformation temperatures. The composite hot processing map delineates optimal process parameters (400°C–450 °C & 0.1s−1-1s−1), facilitating informed decision-making in manufacturing practices. The validation of numerical simulations through TRSR forming experiments with initial temperature of 450 °C for the billet and axial moving speed of 10 mm/s for the chuck in affirms the feasibility of producing hollow stepped shafts from high-strength Al–Zn–Mg–Cu alloy. Close agreement was found between simulated and experimental wall thickness variations. This study enhances understanding and optimization of TRSR forming for high-strength lightweight alloys, advancing industrial manufacturing methodologies.

Abstract Background The association between poor social relationships and post-stroke mortality remains uncertain, and the evidence regarding the relationship between poor social relationships and the risk of stroke is inconsistent. In this meta-analysis, we aim to elucidate the evidence concerning the risk of stroke and post-stroke mortality among individuals experiencing a poor social relationships, including social isolation, limited social networks, lack of social support, and loneliness. Methods A thorough search of PubMed, Embase, and the Cochrane Library databases to systematically identify pertinent studies. Data extraction was independently performed by two researchers. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using either a random-effects or fixed-effects model. Sensitivity analyses were conducted to evaluate the reliability of the results. Random-effects meta-regression was performed to explore the sources of heterogeneity in stroke risk estimates between studies. Assessment for potential publication bias was carried out using Egger’s and Begg’s tests. Results Nineteen studies were included, originating from 4 continents and 12 countries worldwide. A total of 1,675,707 participants contributed to this meta-analysis. Pooled analyses under the random effect model revealed a significant association between poor social relationships and the risk of stroke (OR = 1.30; 95%CI: 1.17–1.44), as well as increased risks for post-stroke mortality (OR = 1.36; 95%CI: 1.07–1.73). Subgroup analyses demonstrated associations between limited social network (OR = 1.52; 95%CI = 1.04–2.21), loneliness (OR = 1.31; 95%CI = 1.13–1.51), and lack of social support (OR = 1.66; 95%CI = 1.04–2.63) with stroke risk. The meta-regression explained 75.21% of the differences in reported stroke risk between studies. Random-effect meta-regression results indicate that the heterogeneity in the estimated risk of stroke may originate from the continent and publication year of the included studies. Conclusion Social isolation, limited social networks, lack of social support, and feelings of loneliness have emerged as distinct risk factors contributing to both the onset and subsequent mortality following a stroke. It is imperative for public health policies to prioritize the multifaceted influence of social relationships and loneliness in stroke prevention and post-stroke care. Trial registration The protocol was registered on May 1, 2024, on the Prospero International Prospective System with registration number CRD42024531036.

Objective This study aimed to investigate the effects of dietary supplementation with Agaricus blazei polysaccharide (ABP) at varying concentrations on the performance, egg quality, blood biochemistry, intestinal morphology, and microflora of quail. Methods The study involved a total of 2,700 Korean quails, which were randomly divided into three groups. The measured variables encompassed productive performance, egg parameters, carcass parameters, serum metabolites, immune response parameters, antioxidative properties, and gut microbiome. Results The addition of ABP did not have a significant effect on average daily feed intake. However, it was found to increase the average daily egg weight and egg production rate, reduce the feed-egg ratio. There were no significant impacts on egg quality measures such as egg shape index, egg yolk index and color, egg yolk and protein content. However, ABP supplementation significantly increased the Hough unit (p

Highlights Asymmetrically coordinated Co–N4–O sites on N-doped carbon nanofiber were prepared. Co–O coordination along the axial direction led to enhanced dielectric polarization loss. Multifunctional films were developed for practical application in harsh environments.

Abstract Background Evidence has shown that the individual metrics in Life’s Essential 8 (LE8), an updated cardiovascular health (CVH) concept proposed by the American Heart Association, play a role in the development of inflammatory bowel disease (IBD). However, epidemiological evidence on the overall LE8 on IBD risk remains limited. We aimed to assess the longitudinal associations of LE8-defined CVH and the risks of IBD and its subtypes, ulcerative colitis (UC) and Crohn’s disease (CD). We also tested whether genetic susceptibility could modify these associations. Methods A total of 260,836 participants from the UK Biobank were included. LE8 scores were determined by 8 metrics (physical activity, diet, nicotine exposure, sleep, body mass index, blood pressure, blood glucose, and blood lipids), and were divided into three levels: low CVH (0–49), moderate CVH (50–79), and high CVH (80–100). Cox proportional hazards models were used to calculate the hazard ratios (HRs) and confidence intervals (CIs) of the risk of IBD in relation to CVH status. Results Over a median follow-up 12.3 years, we documented 1,500 IBD cases (including 1,070 UC and 502 CD). Compared to participants with low CVH, the HRs (95% CIs) of those with high CVH for IBD, UC, and CD were 0.67 (0.52, 0.83), 0.70 (0.52, 0.93), and 0.55 (0.38, 0.80), respectively. These associations were not modified by genetic susceptibility (all P for interactions > 0.05). The lowest HR (UC: 0.30, 95% CI: 0.20–0.45; CD: 0.33, 95% CI: 0.20–0.57) was observed in participants with both high CVH and low genetic risk. Conclusions Better CVH, defined by LE8, was associated with significantly lower risks of IBD, UC, and CD, irrespective of genetic predisposition. Our results underscore the importance of adherence to LE8 guidelines for maintaining CVH as a potential strategy in the prevention of IBD.

The incidence of inflammatory bowel disease (IBD) is rising globally, increasing interest in food ingredients for its prevention and control. This study evaluated the effect of farnesol (FAR), a key component of pomelo flower volatile oil, on dextran sodium sulfate (DSS)-induced colitis in C57BL/6 mice. FAR significantly alleviated DSS-induced colitis and secondary liver injury, as shown by improved body weight, DAI, colon length, and pathology, as well as liver function and blood lipid indices. The mechanism involves FAR-mediated regulation of inflammatory cytokines, increased expression of tight junction protein genes, and decreased expression of lipid metabolism-related proteins. FAR also enhanced gut microbiota diversity, balancing harmful and probiotic bacteria. Fecal metabolome analysis indicated FAR's role in reversing metabolic disturbances related to inflammation and liver lipid metabolism. These findings support developing functional foods for IBD treatment using pomelo flower volatile oil.

Background: Different risk factors are responsible for the occurrence of coronary artery disease (CAD). Among these, the main factors are dyslipidemia, dysglycaemia, and endothelial inflammation. The aim of the study was to analyze the levels of lipids, glucose, and cytokine in patients with different coronary heart diseases. Methods: A total of 2147 patients diagnosed with coronary atherosclerosis, stable angina, unstable angina, acute non-ST-segment elevation infarction (NSTEMI) and acute ST-segment-elevation myocardial infarction (STEMI) at the Cardiovascular Center of Beijing Tongren Hospital from February 2022 to April 2023. The data were gathered from the medical record system.Nonparametric Wilcoxon test was used for statistical analysis of continuous variables, and chi-square test was used for statistical analysis of categorical variables among multiple groups. Results: Compared with coronary atherosclerosis group, acute myocardial infarction group showed a significant increase in IL-6 level (p

Abstract Waterless transport is an alternative method for live aquatic products. However, the changes that occur in the fish body after transportation are not known. Herein, the effects of different transport methods on quality of turbot (Scophthalmus maximus) were investigated. Fish were divided into four groups: Group A (water, 17°C), Group B (waterless, 3°C), Group C (water, 3°C), and Group D (control, 17°C). In the case of 100% survival, the maximum transport time was 40 h for Group A, 55 h for Group B, and 90 h for Group C. Both crude protein and crude fat decreased significantly (p 40 h, regardless of the transport method.

In this work, ginsenoside CK was confirmed as an EGFR tyrosine kinase inhibitor, with an IC50 value of 32.58 ± 0.09 μM. Molecular docking showed that ginsenoside CK could fit into EGFR binding pocket, thereby acting as a ligand for EGFR. Ginsenoside CK inhibited proliferation of A549 cells as well as induced its apoptosis via downregulating anti-apoptotic factors and upregulating apoptosis induction factors. Ginsenoside CK alone and combined with gefitinib inhibited the tumor progression of A549 lung cancer xenografts in BALB/c nude mice. ELISA assay showed that ginsenoside CK combined with gefitinib alleviated the inflammatory response by suppressing the release of pro-inflammatory cytokines, indicating better inhibitory effects than ginsenoside CK or gefitinib alone. This work further confirmed that ginsenoside CK regulated the EGFR/MAPK/ERK signaling both in vitro and in vivo. In conclusion, ginsenoside CK can exhibit the anti-lung cancer effect via acting as an EGFR tyrosine kinase inhibitor.

Abstract Background Carcass traits are crucial indicators of meat production efficiency. However, the molecular regulatory mechanisms associated with these traits remain unclear. Results In this study, we conducted comprehensive transcriptomic and genomic analyses on 399 Tiannong partridge chickens to identify key genes and variants associated with carcass traits and to elucidate the underlying regulatory mechanisms. Based on association analyses with the elastic net (EN) model, we identified 12 candidate genes (AMY1A, AP3B2, CEBPG, EEF2, EIF4EBP1, FGFR1, FOXD3, GOLM1, LOC107052698, PABPC1, SERPINB6 and TBC1D16) for 4 carcass-related traits, namely live weight, dressed weight, eviscerated weight, and breast muscle weight. SERPINB6 was identified as the only overlapping gene by 3 analyses, EN model analysis, weighted gene co-expression network analysis and differential expression analysis. Cell-level experiments confirmed that SERPINB6 promotes the proliferation of chicken DF1 cells and primary myoblasts. Further expression genome-wide association study and association analysis indicated that rs317934171 is the critical site that enhances SERPINB6 expression. Furthermore, a dual-luciferase reporter assay proved that gga-miR-1615 targets the 3′UTR of SERPINB6. Conclusions Collectively, our findings reveal that SERPINB6 serves as a novel gene for chicken carcass traits by promoting fibroblast and myoblast proliferation. Additionally, the downstream variant rs317934171 regulates SERPINB6 expression. These results identify a new target gene and molecular marker for the molecular mechanisms of chicken carcass traits.

Variations in the mechanical properties and pore structure of granulated blast furnace slag self-compacting concrete were studied. The grey correlation theory established the relationship between mechanical properties and pore structure. The test results show that with the continuous improvement of age, the mechanical properties decreased with the increase of sand replacement rate in the early stage. In the middle and late stages, the compressive strength and splitting tensile strength of granulated blast furnace slag self-compacting concrete are higher than those of ordinary self-compacting concrete, while the elastic modulus continues to decrease with increasing slag content. After standard curing, the change in the pore structure parameters of ordinary self-compacting concrete is relatively stable. The pore structure parameters of granulated blast furnace slag self-compacting concrete change significantly. Because granulated blast furnace slag has a certain hydraulicity, the strength and strength growth rate of granulated blast furnace slag self-compacting concrete are higher than those of ordinary self-compacting concrete, and the corresponding pore structure parameters change. Through grey correlation analysis, the specific surface area and average chord length structure of granulated blast furnace slag self-compacting concrete are essential factors affecting its mechanical properties.

To improve the load-bearing capacity and the rotation range about the normal of the moving platform in a spherical parallel mechanism (SPM), a type synthesis method for spherical hybrid mechanisms (SHMs) with fixed centers of rotation is proposed by coupling a serial transmission chain with the central passive limb chain of the SPM near its center area. Based on the analysis of the spherical mechanism configuration’s research status with a fixed rotation center, a method for systematically synthesizing SHMs is given, and four types of limb chains are developed. The possible limb constraint systems provided by each type of limb chain are analyzed via screw theory, and the type synthesis of each type of limb chain is carried out. Screening rules are proposed to obtain the preferred limb chains from the limb chain configuration results. By selecting and permuting preferred limb chains based on the mechanism’s center position of rotation and the constraint type, a series of SHMs that rotate unrestricted about the normal of the moving platform are produced. Selecting the RBR-2RRR SHM as an example, its workspace, singularity, dexterity, and stiffness are analyzed to verify the effectiveness of the research. This work enriches the configuration types of SHMs and provides theoretical support for the design and applications of SHMs in engineering.

Research purpose: This study aims to outline the fundamental status of the German academic community's research in the field of renewable energy and to foster collaboration between China and Germany in this area. Research methods: This study examines documents published by German scholars from 2008 to 2023, which are part of the “Web of Science (WOS) Core Collection” database and related to renewable energy issues, using the bibliometric visualization tool CiteSpace 6.2.R6. Research conclusions: The study examines the co-occurrence and burst of keywords, changes in publication volume, international collaboration networks, research institution collaboration networks, and researcher collaboration networks. It concluded that: (1) German academic research in the field of renewable energy can be divided into three phases: nascent (2008–2014), surge (2015–2021), and decline (2022–2023). (2) The Helmholtz Association and Reinhard Madlener, among other prominent institutions and academicians, are responsible for the close cooperation among personnel and institutions, the significant leading effect, and the emphasis on cutting-edge topics. Research in this field notably focuses on cutting-edge issues like life cycle assessment and developing countries. The study observes a transition in research concentration from macro to micro perspectives. In the context of a global collective response to climate change, the analysis of the German academic community’s overall situation will enhance the collaboration between the two countries in the field of renewable energy research.

With the development of 5G technology and increasing chip integration, traditional active cooling methods struggle to meet the growing thermal demands of chips. Thermoelectric coolers (TECs) have garnered great attention due to their rapid response, significant cooling differentials, strong compatibility, high stability and controllable device dimensions. In this review, starting from the fundamental principles of thermoelectric cooling and device design, high-performance thermoelectric cooling materials are summarized, and the progress of advanced on-chip TECs is comprehensively reviewed. Finally, the paper outlines the challenges and opportunities in TEC design, performance and applications, laying great emphasis on the critical role of thermoelectric cooling in addressing the evolving thermal management requirements in the era of emerging chip technologies.

Summary: Amygdala serves as a highly cellular, heterogeneous brain region containing excitatory and inhibitory neurons and is involved in the dopamine and serotoninergic neuron systems. An increasing number of studies have revealed the underpinned mechanism mediating social hierarchy in mammal and vertebrate, however, there are rare studies conducted on how amygdala on social hierarchy in poultry. In this study, we conducted food competition tests and determined the social hierarchy of the rooster. We performed cross-species analysis with mammalian amygdala, and found that cell types of human and rhesus monkeys were more closely related and that of chickens were more distant. We identified 26 clusters and divided them into 10 main clusters, of which GABAergic and glutamatergic neurons were associated with social behaviors. In conclusion, our results provide to serve the developmental studies of the amygdala neuron system and new insights into the underpinned mechanism of social hierarchy in roosters.

Abstract Social recognition encompasses encoding social information and distinguishing unfamiliar from familiar individuals to form social relationships. Although the medial prefrontal cortex (mPFC) is known to play a role in social behavior, how identity information is processed and by which route it is communicated in the brain remains unclear. Here we report that a ventral midline thalamic area, nucleus reuniens (Re) that has reciprocal connections with the mPFC, is critical for social recognition in male mice. In vivo single-unit recordings and decoding analysis reveal that neural populations in both mPFC and Re represent different social stimuli, however, mPFC coding capacity is stronger. We demonstrate that chemogenetic inhibitions of Re impair the mPFC-Re neural synchronization and the mPFC social coding. Projection pathway-specific inhibitions by optogenetics reveal that the reciprocal connectivity between the mPFC and the Re is necessary for social recognition. These results reveal an mPFC-thalamic circuit for social information processing.

Extremely large aperture array (ELAA) represents a paradigm shift in wireless antenna systems, poised to redefine the capabilities of future networks, particularly in the era of the sixth generation (6G) networks. The integration of multiple-input multiple-output (MIMO) technology with an unprecedented scale of antenna arrays enables transformative potential for enhancing spectral efficiency, increasing coverage, and enabling new applications. This paper provides a comprehensive overview of ELAA, delving into fundamental concepts, state-of-the-art technologies, and practical applications. We commence by presenting the fundamentals of ELAA technology, focusing on the various architectural categories and two fundamental properties of communication in the near-field region of ELAA, namely spherical wave propagation and channel spatial non-stationarity. We then illustrate the phenomenon of finite beam depth in the near field before presenting general distance boundaries based on various criteria and conducting a comprehensive performance analysis of this technology. Subsequently, in light of the distinctive electromagnetic characteristics of ELAA, we will examine the practical challenges that have emerged, including channel estimation, beamforming design, and the practical hardware issues that have arisen. Subsequently, we examine the diverse applications of ELAA across various domains, emphasizing its transformative potential in fields such as physical layer security, communication and sensing, and wireless power and information transfer. Finally, the paper concludes by outlining several promising avenues for future research and exploration within the realm of ELAA. These avenues are identified as areas ripe for investigation and innovation.

Sudden stratospheric warming (SSW) is a violent atmospheric disturbance in the polar region of the winter hemisphere. The drastic changes in temperature and wind during SSWs are considered to be the main reasons for the abnormal increase in the energy of atmospheric waves in the upper and middle atmosphere in the winter hemisphere. Meteor radar is an important ground-based detection equipment that can stably and continuously detect neutral wind in the mesosphere and lower thermosphere (MLT) region. Based on one of the National Major Science Infrastructure Projects, the "Meridian Project", China has built several meteor radar observation stations to conduct long-term stable and continuous monitoring of the neutral wind in the MLT region, which provides important observation data for revealing the physical mechanism of abnormal changes in atmospheric waves during SSWs. Here, we briefly review the research progress on planetary waves in the middle and upper atmosphere during SSWs in recent years, especially the scientific findings based on the meteor radars in the Chinese "Meridian Project". The trigger mechanisms of the enhanced planetary waves during SSWs are discussed. With the completion of ten meteor radars in the second phase of the "Meridian Project", this paper prospects the use of its meteor radar monitoring network to further study the characteristics of atmospheric waves in the middle and upper atmosphere during SSWs.

Linoleic acid is an essential polyunsaturated fatty acid that cannot be synthesized by humans or animals themselves and can only be obtained externally. The amount of linoleic acid present has an impact on the quality and flavour of meat and indirectly affects consumer preference. However, the molecular mechanisms influencing the deposition of linoleic acid in organisms are not clear. As the molecular mechanisms of linoleic acid deposition are not well understood, to investigate the main effector genes affecting the linoleic acid content, this study aimed to screen for hub genes in slow-type yellow-feathered chickens by transcriptome sequencing (RNA-Seq) and weighted gene coexpression network analysis (WGCNA). We screened for candidate genes associated with the linoleic acid content in slow-type yellow-feathered broilers. A total of 399 Tiannong partridge chickens were slaughtered at 126 days of age, fatty acid levels were measured in pectoral muscle, and pectoral muscle tissue was collected for transcriptome sequencing. Transcriptome sequencing results were combined with phenotypes for WGCNA to screen for candidate genes. KEGG enrichment analysis was also performed on the genes that were significantly enriched in the modules with the highest correlation. A total of 13 310 genes were identified after quality control of transcriptomic data from 399 pectoral muscle tissues. WGCNA was performed, and a total of 26 modules were obtained, eight of which were highly correlated with the linoleic acid content. Four key genes, namely, MDH2, ATP5B, RPL7A and PDGFRA, were screened according to the criteria |GS|>0.2 and |MM|>0.8. The functional enrichment results showed that the genes within the target modules were mainly enriched in metabolic pathways. In this study, a large-sample-size transcriptome analysis revealed that metabolic pathways play an important role in the regulation of the linoleic acid content in Tiannong partridge chickens, and MDH2, ATP5B, RPL7A and PDGFRA were screened as important candidate genes affecting the linoleic acid content. The results of this study provide a theoretical basis for selecting molecular markers and comprehensively understanding the molecular mechanism affecting the linoleic acid content in muscle, providing an important reference for the breeding of slow-type yellow-feathered broiler chickens.

Geomagnetic storms can cause large variations in the ionosphere, but their impacts on the mesosphere and lower thermosphere (MLT) are not well understood. Based on the Total Electron Content (TEC) data and the meteor neutral winds data over Mohe (53.5°N, 122.3°E) and Beijing (40.3°N, 116.2°E), we analyze the tidal variations during six intense geomagnetic storms from 2016 to 2021. According to the six intense geomagnetic storms, we found that intense geomagnetic storms can lead to diurnal and semidiurnal tidal enhancements in TEC, while their influences on tidal variations in the MLT region are not always captured. Responses of tidal enhancement in the MLT region to the intense geomagnetic storms are more obvious at a lower latitude at Beijing, but the tidal amplitude changes are not proportional to the Dst indices. Some semidiurnal tides are significantly enhanced prior to the onset of geomagnetic storms, which needs to be statistically investigated in the future based on additional observations.

Electrostatic fields are crucial for achieving the highly efficient filtration of airborne pollutants. However, the dissipation of static charges over time, especially under humid conditions, limits their practical application. In this study, we present a self-charging air filter (SAF) powered by a triboelectric nanogenerator (TENG). This SAF is integrated into a commercial mask, termed SAFM, which can effectively capture and degrade airborne pollutants without requiring an external power source. By leveraging the triboelectric effect during breathing, the TENG within the SAFM continuously replenishes static charges, maintaining the triboelectric field. The system employs a cellulose aerogel/Ti3C2Tx composite as the electron donor and an esterified cellulose-based electrospun nanofiber as the electron acceptor. Remarkably, the triboelectric field significantly enhances filtration performance, with the SAF achieving up to 95.7% filtration efficiency for particulate matter as small as 0.3 μm. This work underscores the potential of TENG-powered triboelectric fields in the development of multifunctional, human-machine interactive facemasks.

Krüppel-like factors (KLFs) are a class of fundamental transcription factors that are widely present in various eukaryotes from nematodes to humans, named after their DNA binding domain which is highly homologous to the Krüppel factor in fruit flies. To investigate the composition, organization, and evolutionary trajectory of KLF gene family members in chickens, in our study, we leveraged conserved sequences of KLF genes from representative classes across fish, amphibians, birds, and mammals as foundational sequences. Bioinformatic tools were employed to perform homology alignment on the chicken genome database, ultimately identifying the KLF family members present in chickens. The gene structure, phylogenetic analysis, conserved base sequences, physicochemical properties, collinearity analysis, and protein structure were then analyzed using bioinformatic tools. Additionally, the impact of miRNA-22, related to poultry lipid metabolism, on the expression of the KLF gene family in the liver, heart, and muscle of Qingyuan partridge chickens was explored. The results showed that: (1) compared to fish, the KLF family in birds is more closely related to mammals and amphibians; (2) KLFs within the same subgroups are likely to be derived from a common ancestral gene duplication; (3) KLF3/8/12 in the same subgroup may have some similar or overlapping functions; (4) the motif 4 of KLF5 was most likely lost during evolution; (5) KLF9 may perform a similar function in chickens and pigs; (6) there are collinear relationships between certain KLF genes, indicating that there are related biomolecular functions between these KLF genes; (7) all members of the KLF family in chickens are non-transmembrane proteins; and (8) interference and overexpression of miRNA-22 in Qingyuan partridge chickens can affect the expression levels of KLF genes in liver, heart, and muscle.

Sex determination in chickens at an early embryonic stage has been a longstanding challenge in poultry production due to the unique ZZ:ZW sex chromosome system and various influencing factors. This review has summarized the genes related to the sex differentiation of chicken early embryos (mainly Dmrt1, Sox9, Amh, Cyp19a1, Foxl2, Tle4z1, Jun, Hintw, Ube2i, Spin1z, Hmgcs1, Foxd1, Tox3, Ddx4, cHemgn and Serpinb11 in this article), and has found that these contributions enhance our understanding of the genetic basis of sex determination in chickens, while identifying potential gene targets for future research. This knowledge may inform and guide the development of sex screening technologies for hatching eggs and support advancements in gene-editing approaches for chicken embryos. Moreover, these insights offer hope for enhancing animal welfare and promoting conservation efforts in poultry production.

Abstract The transition to green energy systems is vital for addressing climate change, with a focus on renewable sources like wind and solar. This change requires substantial investment, societal adaptations, and managing a complex energy ecosystem. However, no existing evaluation methods support this purpose. The "energy metaverse" is proposed as a digital platform that mirrors the energy ecosystem, enabling the design, trial, and assessment of new technologies, business models, and value chains before real-world deployment. Drawing from State-of-the-Art technologies and methodologies, this paper introduces a conceptual framework for the energy metaverse, comprising five essential components: a versatile energy ecosystem data space, an interoperable virtual ecosystem living lab, an energy system models and artificial intelligent algorithms sandbox, a circular value chain co-design toolbox, and an ecosystem lifecycle evaluation software tool. This paper also suggests specific methods and technologies to develop each of these five components of the energy metaverse.

Abstract Modulation of magnetic properties through voltage-driven ion motion and redox processes, i.e., magneto-ionics, is a unique approach to control magnetism with electric field for low-power memory and spintronic applications. So far, magneto-ionics has been achieved through direct electrical connections to the actuated material. Here we evidence that an alternative way to reach such control exists in a wireless manner. Induced polarization in the conducting material immersed in the electrolyte, without direct wire contact, promotes wireless bipolar electrochemistry, an alternative pathway to achieve voltage-driven control of magnetism based on the same electrochemical processes involved in direct-contact magneto-ionics. A significant tunability of magnetization is accomplished for cobalt nitride thin films, including transitions between paramagnetic and ferromagnetic states. Such effects can be either volatile or non-volatile depending on the electrochemical cell configuration. These results represent a fundamental breakthrough that may inspire future device designs for applications in bioelectronics, catalysis, neuromorphic computing, or wireless communications.

Abstract Starch is the most important component in potato tubers, whose structure and composition play key roles in properties of potato storage, processing, and applications. This review identifies the biodiversity of starch content, structure, and physiochemical properties, particularly the amylose and amylopectin content, molecular and granular structure, gelatinization, retrogradation, swelling power, solubility, and digestibility of potato in the past decade. Various functions of major potato starch biosynthesis‐related enzymes, such as AGPase, starch synthase, starch branching enzyme, debranching enzyme, and glucan/water dikinase, are also summarized. The potential utilization of native and modified potato starch in food and medicine fields owing to its high pasting viscosity is also analyzed. This review will contribute to a better understanding of the genetics–structure–functions of potato starch and may provide insights into potential potato starch utilization and further genetic improvement of starch quality.

Abstract Rhodophyta are among the closest known relatives of green plants. Studying the codons of their genomes can help us understand the codon usage pattern and characteristics of the ancestor of green plants. By studying the codon usage pattern of all available red algae, it was found that although there are some differences among species, high-bias genes in most red algae prefer codons ending with GC. Correlation analysis, Nc-GC3s plots, parity rule 2 plots, neutrality plot analysis, differential protein region analysis and comparison of the nucleotide content of introns and flanking sequences showed that the bias phenomenon is likely to be influenced by local mutation pressure and natural selection, the latter of which is the dominant factor in terms of translation accuracy and efficiency. It is worth noting that selection on translation accuracy could even be detected in the low-bias genes of individual species. In addition, we identified 15 common optimal codons in seven red algae except for G. sulphuraria for the first time, most of which were found to be complementary and bound to the tRNA genes with the highest copy number. Interestingly, tRNA modification was found for the highly degenerate amino acids of all multicellular red algae and individual unicellular red algae, which indicates that highly biased genes tend to use modified tRNA in translation. Our research not only lays a foundation for exploring the characteristics of codon usage of the red algae as green plant ancestors, but will also facilitate the design and performance of transgenic work in some economic red algae in the future.

An accurate constitutive model is imperative to describe the deformation behavior of aluminum alloy in numerical simulation of thermal plastic forming process. In this study, isothermal uniaxial compressions of 2A12-T4 aluminum alloy were conducted by Gleeble-3500 thermal-mechanical simulator under the temperature of 300–450 °C and strain rate of 0.01–10 s−1. Three different Arrhenius constitutive models, including strain compensation (SC), genetic algorithm (GA) and K-function modification (KM), were established basing on the double correction of the true stress–strain curve by considering the effect of temperature variation and interfacial friction. The prediction accuracy of three models were assessed by the correlation coefficient (R), average absolute relative error (AARE) and the logarithm of the mean square error (ln (MSE)). The results show that the newly KM constitutive model considering the coupling effect of temperature and strain rate showed excellent agreement with the experimental data and best prediction capability with lowest error. Hot processing map based on the Murty-Rao criterion shows that high temperature and low strain rate is suitable for stable forming. In order to verify the reliability of the proposed model in numerical simulation, the established KM Arrhenius constitutive equation is secondarily developed in DEFORM 3D software and used in the hot compression process under the stable forming conditions obtained from hot processing map. The simulated force–displacement curves and maximum load values under forming conditions were well match with the experiment trends, which proved the reliability of the KM constitutive equation in the finite element numerical simulation.

Drought stress is one of the major impediments to plant growth. Plant growth-promoting rhizobacteria (PGPR) can mitigate moisture stress in plants by increasing the ability of plant nutrient uptake and transport. In this study, we investigated the root phenotype, mineral nutrients (in leaves, roots, and soil), soil pH, water saturation deficit (WSD), free water content (FWC), and bound water content (BWC) of leaves of two alfalfa varieties, ‘Galalxie Max’ (drought-tolerant) and ‘Saidi 7’ (drought-sensitive), in the presence or absence of Bacillus amyloliquefaciens QST713 under drought stress conditions. The results showed that water stress negatively affected both cultivar root morphology (total root length, average diameter, total surface area, and volume) and the contents of K and Fe in leaves, roots, and soil. It also reduced the Mn and Zn contents in the soil while increasing the content of Na in the leaves and soil. Additionally, alfalfa plants under drought stress exhibited higher levels of soil pH, WSD, and BWC but lower contents of FWC and ratios of BWC/FWC in the leaves of both cultivars. However, QST713 application significantly enhanced the total root length, average root diameter, and the contents of K and Fe in alfalfa leaves, roots, and soil, as well as the BWC/FWC ratio in leaves under drought stress conditions. A significant reduction in the Na content was detected in QST713-treated alfalfa leaves and soil under drought stress. Furthermore, QST713 application noticeably decreased soil pH and WSD. The current findings showed that QST713 enhanced the water stress tolerance of alfalfa plants by ameliorating root morphology, reducing soil pH, and improving the BWC/FWC ratio, consequently promoting the accumulation of mineral nutrients (mainly K and Fe). Overall, Bacillus amyloliquefaciens QST713 can serve as a potential green fertilizer in sustainable agriculture to improve soil nutrients and enhance plant production under increasing drought conditions.

The rational design, activity prediction, and adaptive application of biological elements (bio-elements) are crucial research fields in synthetic biology. Currently, a major challenge in the field is efficiently designing desired bio-elements and accurately predicting their activity using vast datasets. The advancement of artificial intelligence (AI) technology has enabled machine learning and deep learning algorithms to excel in uncovering patterns in bio-element data and predicting their performance. This review explores the application of AI algorithms in the rational design of bio-elements, activity prediction, and the regulation of transcription-factor-based biosensor response performance using AI-designed elements. We discuss the advantages, adaptability, and biological challenges addressed by the AI algorithms in various applications, highlighting their powerful potential in analyzing biological data. Furthermore, we propose innovative solutions to the challenges faced by AI algorithms in the field and suggest future research directions. By consolidating current research and demonstrating the practical applications and future potential of AI in synthetic biology, this review provides valuable insights for advancing both academic research and practical applications in biotechnology.

The liver of chickens is essential for maintaining physiological activities and homeostasis. This study aims to investigate the specific function and molecular regulatory mechanism of microRNA-122 (miR-122), which is highly expressed in chicken liver. A lentivirus-mediated overexpression vector of miR-122 was constructed and used to infect 12-day-old female Qingyuan Partridge chickens. Transcriptome sequencing analysis was performed to identify differentially expressed genes in the liver. Overexpression of miR-122 resulted in 776 differentially expressed genes (DEGs). Enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) revealed associations with lipid metabolism, cellular senescence, cell adhesion molecules, and the MAPK signaling pathway. Eight potential target genes of miR-122 (ARHGAP32, CTSD, LBH, PLEKHB2, SEC14L1, SLC2A1, SLC6A14, and SP8) were identified through miRNA target prediction platforms and literature integration. This study provides novel insights into the molecular regulatory mechanisms of miR-122 in chicken liver, highlighting its role in key biological processes and signaling pathways. These discoveries enhance our understanding of miR-122’s impact on chicken liver function and offer valuable information for improving chicken production performance and health.

Abdominal fat deposition (AFD) in chickens is closely related to the gut microecological balance. In this study, the gut microbiota from high-AFD chickens was transplanted into the same strain of 0-day-old chicks via fecal microbiota transplantation (FMT). The FTM from chickens with high AFD had no obvious effects on growth traits, adult body weight, carcass weight, abdominal fat weight, and abdominal fat percentage, but did reduce the coefficient of variation of AFD traits. FMT significantly decreased cecal microbiome richness, changed the microbiota structure, and regulated the biological functions associated with energy metabolism and fat synthesis. Additionally, the cecal metabolite composition and metabolic function of FMT recipient chickens were also significantly altered from those of the controls. Transplantation of high-AFD chicken gut microbiota promoted fatty acid elongation and biosynthesis and reduced the metabolism of vitamins, steroids, and carbohydrates in the cecum. These findings provide insights into the mechanisms by which chicken gut microbiota affect host metabolic profiles and fat deposition.

Introduction Long head of biceps brachii tendinopathy (LHBT) is characterised by persistent pain and disability of shoulder joint, impairing patients’ quality of life. Extracorporeal shock wave therapy (ESWT) is a non-invasive treatment, which promotes tissue regeneration and repair. However, ESWT has a side effect that often causes short-term pain and swelling in the treatment area. It is known that the effects of Kinesio taping (KT) on relieving swelling and pain. Due to insufficient clinical evidence from current limited studies, this randomised controlled study aims to explore the effects of ESWT combined with KT on upper limb function during individuals with LHBT.Methods and analysis A 2×2 factorial design, double-blind, randomised controlled trial will be conducted. A total of 144 participants will be randomly allocated into one of four groups (KT+ESWT, KT+sham ESWT, sham KT+ESWT or sham KT+sham ESWT) to participate in a 4-week treatment programme. Measurements will be taken at pretreatment (baseline), immediately after treatment and 6 weeks after treatment. The primary endpoint will be the Constant-Murley score (CMS), the secondary endpoints will include the pain Numerical Rating Scale, range of motion, pressure pain threshold and soft tissue hardness of biceps, speed test and global rating of change. Repeated measures analysis of variance will be used to compare differences among the effects of different interventions.Ethics and dissemination Ethics approval was obtained from the Ethics Committee of the Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. In addition to international conference reports, findings will be disseminated through international publications in peer-reviewed journals.Trial registration number ChiCTR2100051324.

Abstract Using a clustering algorithm based on cloud‐to‐ground (CG) lighting data, 72,974 thunderstorms were identified and tracked in the middle reaches of the Yangtze River Basin from May to September of 2016–2020. Thunderstorms predominantly occur in the southeast region and move to the northeast at a speed of 16–64 km/hr. Most thunderstorms have short durations (98.3%, ≤3 hr) and low CG flash frequencies (90.0%, ≤64). Thunderstorms with longer durations are mainly triggered near the mountains and tend to occur (end) earlier (later) in the afternoon (evening). The peak composite reflectivity (CR) corresponding to CG flashes from all thunderstorms is 50 dBZ. Approximately 70% (20%) of CG flashes occur in convective (stratiform) areas. The first CG flash of a thunderstorm tends to occur in convective areas with a higher CR than that of the last CG flash. The average and maximum CRs of CG flashes increase significantly with thunderstorm duration.

BackgroundThe progression of early stage non-small cell lung cancer (NSCLC) is closely related to epidermal growth factor receptor (EGFR) mutation status. The purpose of this study was to systematically investigate the relationship between EGFR mutation status and demographic, imaging, and ultimately pathologic features in patients with NSCLC.MethodsA complete literature search was conducted using the PubMed, Web of Science, EMBASE, and Cochrane Library databases to discover articles published by May 15, 2023 that were eligible. The relationship between EGFR mutation status and specific demographic, imaging, and ultimately pathologic features in patients with NSCLC was evaluated using pooled odds ratios (ORs) and their 95% confidence intervals (CIs). The standardized mean difference (SMD) with 95% CIs was the appropriate statistic to summarize standard deviations (SDs) means for continuous variables.ResultsA total of 9 studies with 1789 patients were included in this analysis. The final findings suggested that patients with a greater age, female gender, and non-smoking status would have a relatively higher incidence of EGFR mutations. Additionally, the risk of EGFR mutations increased with larger tumor diameter, tumor imaging presentation of mixed ground glass opacity (mGGO), and tumor pathological findings of minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IAC). Significantly, malignancies presenting as MIA are more likely to contain L858R point mutations (OR = 1.80; 95% CI: 1.04–3.13; p = 0.04) rather than exon 19 deletions (OR = 1.81; 95% CI: 0.95–3.44; p = 0.07).ConclusionThis meta-analysis showed that imaging parameters and histological classifications of pulmonary nodules may be able to predict stage IA NSCLC genetic changes.

Abstract Low-frequency magnetic fields exert a significant inhibitory effect on tumor growth and have been developed as a therapeutic modality. However, the effect of a low-frequency magnetic field on the interaction between cells is still poorly understood. This study aimed to preliminarily evaluate the direct effect of magnetic field ditectely on cultured cells and indirect effect mediated by cell-environment (conditioned medium). 293 T cells, Hepg2 cells, A549 cells have been cultured at 37 ± 0.18 °C in presence of an extremely low-frequency magnetic field of 20 Hz, 5-mT. The adherent tumor cells were more sensitive to magnetic field inhibition in the original environment (conditioned medium) with adherence inhibition rate for Hepg2 and A549 estimated at 18% and 30% respectively. The inhibition effect was suppressed when the suspended cells separated or clump density at a low density. The nontumor cell lines showed no inhibitory effect on exposure to a low-frequency magnetic field. The intracellular ion fluorescence (IIF) showed that the magnetic field significantly altered the membrane potential, indicating hyperpolarization of the adherent cells (ΔIIF 293 T cells: − 25%, ΔIIF Hepg2 cells: − 20% and ΔIIF A549 cells: − 13%) and depolarization of the suspended cells (ΔIIF Raji cells: + 9%). In addition, the conditioned media collected after magnetic field exposure acted on unexposed tumor cells and caused inhibition. Our findings might provide a basis for the mechanism of magnetic field interaction between cells and cell environment in the future.

As the adoption of distributed energy resources (DERs) grows, the future of electricity distribution systems is confronted with significant challenges. These challenges arise from the transformation of consumers into prosumers and the resulting increased system complexity, leading to more pressure on the distribution grids. To address this complexity, a Digital Twin framework is designed to simulate DERs within distribution grids effectively. This framework is structured around four key modules: DERs, the electricity distribution grid, the energy management system, and the consumers. It incorporates a communication interface to facilitate interactions among these modules and includes considerations for grid topologies and demand-side configurations. The framework allows for the exploration of various DER adoption rates and capacities. The validation of this framework involves case studies on two Danish distribution grids with scenarios incorporating rooftop photovoltaic (PV) systems, batteries, and electric vehicles, considering different combinations of these technologies. The findings demonstrate the framework’s ability to depict the states of the grid, PV systems, electric vehicles, and battery systems with a 10 min resolution over periods ranging from a day to over a decade.

With the continuous technological innovation in the high-value utilization of rice bran byproducts, rice bran oil retains a higher concentration of beneficial components such as a well-balanced composition of fatty acids and abundant phytosterols. This makes it a highly nutritious and healthy vegetable oil. This review provides an overview of the advancements made in separating, purifying, and processing phytosterols in rice bran oil. The review also introduces techniques for assessing the stability of rice bran oil. Moreover, the review emphasizes the nutritional value of phytosterols found in rice bran oil, highlighting their various health benefits, including their anticancer, anti-inflammatory, anti-allergic, antibacterial, cholesterol-lowering, skin-protective, anti-obesity, anti-diabetic, neuroprotective, gastroprotective, and immune-enhancing effects. Attaining a comprehensive understanding of the research progress made in phytosterols derived from rice bran oil can offer valuable guidance for the efficient utilization of rice bran.

Yu-Ping-Feng polysaccharides (YPF-P) is the primary component of Yu-Ping-Feng San (YPF-S) medicine prescription, which consists of three polysaccharides from Astragalus Membranaceus polysaccharide (AM-P), Atractylodes Macrocephala polysaccharide (AM-P), and Saposhnikovia Divaricata polysaccharide (SD-P). The use of Yu-Ping-Feng polysaccharides dates back to the Yuan Dynasty when Yilin Wei first utilized it. The remedy is included in “Effective Formulae Handed Down for Generations” and “The Pharmacopoeia of the People’s Republic of China.” Yu-Ping-Feng polysaccharides is known to promote growth and enhance the body’s immune function in animals. As such, it has promising application prospects in animal husbandry. This review mainly introduces the main components and characteristics of Yu-Ping-Feng polysaccharides, its effects on animal production, and its impact on animal immune function. Additionally, this paper offers a preliminary discussion on the development and utilization of Yu-Ping-Feng polysaccharides, laying the foundation for further research and application. This review may also provide insight and reference for the development of the farming industry, reducing production costs and improving productivity.

BackgroundAt present, how to identify the benign or malignant nature of small (≤ 2 cm) solitary pulmonary nodules (SPN) are an urgent clinical challenge. This retrospective study aimed to develop a clinical prediction model combining clinical and radiological characteristics for assessing the probability of malignancy in SPNs measuring ≤ 2 cm.MethodIn this study, we included patients with SPNs measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to December 2021. Clinical features, preoperative biomarker results, and computed tomography characteristics were collected. The enrolled patients were randomized at a ratio of 7:3 into a training cohort of 775 and a validation cohort of 331. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. The receiver operating characteristic (ROC) curve was used to evaluate the identification ability of the model. The calibration power was evaluated using the Hosmer–Lemeshow test and calibration curve. The clinical utility of the nomogram was also assessed by decision curve analysis (DCA).ResultA total of 1,106 patients were included in this study. Among them, the malignancy rate of SPNs was 85.08% (941/1,106). We finally identified the following six independent risk factors by logistic regression: age, carcinoembryonic antigen, nodule shape, calcification, maximum diameter, and consolidation-to-tumor ratio. The area under the ROC curve (AUC) for the training cohort was 0.764 (95% confidence interval [CI]: 0.714–0.814), and the AUC for the validation cohort was 0.729 (95% CI: 0.647–0.811), indicating that the prediction accuracy of nomogram was relatively good. The calibration curve of the predictive model also demonstrated a good calibration in both cohorts. DCA proved that the clinical prediction model was useful in clinical practice.ConclusionWe developed and validated a predictive model and nomogram for estimating the probability of malignancy in SPNs measuring ≤ 2 cm. With the application of predictive models, thoracic surgeons can make more rational clinical decisions while avoiding overtreatment and wasting medical resources.

Abstract Background Streoptomyces rimosus M527 is a producer of the polyene macrolide rimocidin which shows activity against various plant pathogenic fungi. Notably, the regulatory mechanisms underlying rimocidin biosynthesis are yet to be elucidated. Results In this study, using domain structure and amino acid alignment and phylogenetic tree construction, rimR2, which located in the rimocidin biosynthetic gene cluster, was first found and identified as a larger ATP-binding regulators of the LuxR family (LAL) subfamily regulator. The rimR2 deletion and complementation assays were conducted to explore its role. Mutant M527-ΔrimR2 lost its ability to produce rimocidin. Complementation of M527-ΔrimR2 restored rimocidin production. The five recombinant strains, M527-ER, M527-KR, M527-21R, M527-57R, and M527-NR, were constructed by overexpressing rimR2 gene using the promoters permE*, kasOp*, SPL21, SPL57, and its native promoter, respectively, to improve rimocidin production. M527-KR, M527-NR, and M527-ER exhibited 81.8%, 68.1%, and 54.5% more rimocidin production, respectively, than the wild-type (WT) strain, while recombinant strains M527-21R and M527-57R exhibited no obvious differences in rimocidin production compared with the WT strain. RT-PCR assays revealed that the transcriptional levels of the rim genes were consistent with the changes in rimocidin production in the recombinant strains. Using electrophoretic mobility shift assays, we confirmed that RimR2 can bind to the promoter regions of rimA and rimC. Conclusion A LAL regulator RimR2 was identified as a positive specific-pathway regulator of rimocidin biosynthesis in M527. RimR2 regulates the rimocidin biosynthesis by influencing the transcriptional levels of rim genes and binding to the promoter regions of rimA and rimC.

Abstract Energy systems face challenges due to climate change, distributed energy resources, and political agenda, especially distribution system operators (DSOs) responsible for ensuring grid stability. Accurate predictions of the electricity load can help DSOs better plan and maintain their grids. The study aims to test a systematic data identification and selection process to forecast the electricity load of Danish residential areas. The five-ecosystem CSTEP framework maps relevant independent variables on the cultural, societal, technological, economic, and political dimensions. Based on the literature, a recurrent neural network (RNN), long-short-term memory network (LSTM), gated recurrent unit (GRU), and feed-forward network (FFN) are evaluated and compared. The models are trained and tested using different data inputs and forecasting horizons to assess the impact of the systematic approach and the practical flexibility of the models. The findings show that the models achieve equal performances of around 0.96 adjusted R2 score and 4–5% absolute percentage error for the 1-h predictions. Forecasting 24 h gave an adjusted R2 of around 0.91 and increased the error slightly to 6–7% absolute percentage error. The impact of the systematic identification approach depended on the type of neural network, with the FFN showing the highest increase in error when removing the supporting variables. The GRU and LSTM did not rely on the identified variables, showing minimal changes in performance with or without them. The systematic approach to data identification can help researchers better understand the data inputs and their impact on the target variable. The results indicate that a focus on curating data inputs affects the performance more than choosing a specific type of neural network architecture.

Abstract Worldwide, buildings consume about 40 percent of the overall energy resources and contribute to an average of 30 percent of the global carbon emission. Hence, technologies for improving the energy efficiency of buildings play an essential role in the global fight against climate change. The CELSIUS project aims to improve the energy efficiency and indoor climate of medium to large sized commercial and public buildings by developing an integrated system solution that consists of (1) an IoT-enabled and cloud-based platform for monitoring and diagnostics of building energy performance and indoor climate quality, (2) a middleware software platform for cost-effective large-scale deployment of wireless sensors and gateways, and (3) an IoT network management platform for cost-efficient life-cycle maintenance of sensors and gateways. The integrated system solution will be deployed and demonstrated in a 6000 m2 building in Aarhus, Denmark, and an 18,000 m2 building in Kuala Lumpur, Malaysia. By choosing buildings located in different climate zones on different continents allows the developed system solution to be tested under realistic conditions for the international export market.

Abstract Digital twin technologies have become popular in wind energy for monitoring and what-if scenario investigation. However, developing a digital representation of the wind is challenging, especially due to the digital twin platform constraints. Game engines might be possible to solve this issue, especially since game engines have been used for product design, testing, prototyping, and also digital twins. Therefore, this study investigates the potential of developing a digital twin of wind power in the Unreal game engine. A case study of two types of wind turbines (Vestas V164-8 and Enercon E-126 7.580) and one location (Esbjerg, Denmark) is chosen for this study. The digital twin includes the environment with historical wind data and the visual representation of the wind turbine with a wind power production model and the estimated production in the given wind conditions of the area. The results show that game engines are viable for building entire digital twins where a realistic graphical user interface is required. Unreal Engine 5 provides the tools for modelling the landscape, surrounding water, and lighting. In addition, the Unreal Engine ecosystem provides vast amounts of content, such as 3D assets and game logic plugins, easing the digital twin development. The results prove that digital twins built in Unreal Engine 5 have great potential development of digital twins and user interfaces for communicating with a digital twin. The developed digital twin allows for further extension to benefit future digital twins utilizing wind turbines.

Abstract Understanding the local needs and challenges is critical for technology adoption in the energy sector. However, it is still a big challenge for most ecosystem stakeholders. Furthermore, technology adoption theories have mainly focused on the technology itself, and the business ecosystem perspective has been neglected. Therefore, this paper proposes an ecosystem-driven business opportunity identification method, a systematic approach for ecosystem stakeholders to conduct business opportunity analysis and evaluation based on the CSTEP ecosystem analysis and evaluation method. This method includes four correlated steps: Step 1: Identify the five CSTEP dimensions of the business ecosystem; Step 2: Identify potential changes in the business ecosystem; Step 3: Identify future ecosystem trends and timeline; Step 4: Select business opportunities; and Step 5: Potential solution identification. A web-based tool called opportunity identifier is developed for implementing the proposed method. A case study of the electric vehicle (EV) home charging energy ecosystem in Denmark is applied and demonstrates the application of the proposed method and the implementation of the developed web-based tool. Three value propositions are identified in the case study: (1) EV users can have optimal EV charging cost and optimal CO2 emission consumption with the intelligent EV charging algorithms that consider electricity prices, tariffs, and CO2 emission; (2) DSOs can avoid grid overloads and postpone the grid upgrade by applying intelligent EV charging algorithms; (3) Independent aggregators can aggregate EVs and participate in the ancillary service market or provide Vehicle-to-Grid services by using intelligent EV charging algorithms. Moreover, three feasible decentralized EV charging strategies (Real Time Pricing, Time-of-Use Pricing, and Timed charging) are identified as the potential solutions targeting the first value proposition.