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The antisolvent‐assisted spin‐coating still lags behind the thermal evaporation method in fabricating perovskite films atop industrially textured silicon wafers in making monolithic perovskite/silicon solar cells (P/S‐TSCs). The inhomogeneity of hole‐selective self‐assembled monolayers (SAMs) often arises from the insufficient bonding between hygroscopic phosphonic acid anchors and metal oxide. To address this, a mixed‐SAM strategy (Mx‐SAM) is proposed to enhance the adsorption energy of SAMs on the ITO surface, facilitate the formation of dense and humidity‐resistant hole‐selective layer (HSL) on substrates, and improve hole transport capabilities. With the aid of the Mx‐SAM strategy, the optimized wide‐bandgap PSCs achieved an impressive power conversion efficiency (PCE) of 22.63% with an exceptionally high fill factor (FF) of 86.67% using the 1.68 eV perovskite. Moreover, they exhibited enhanced stability under damp‐heat conditions (ISOS‐D‐3, 85% RH, 85 °C) with a T90 of 900 h for encapsulated PSCs, representing one of the best performances for wide‐bandgap PSCs. When further extending the Mx‐SAM strategy to making P/S‐TSCs using silicon wafers from industry, a remarkable efficiency of 28.07% is reached while upholding outstanding reproducibility. This strategy holds significant promise for the feasibility of fabricating industrially‐compatible P/S‐TSCs. [ABSTRACT FROM AUTHOR]

Background Purposes Methods Results Conclusions Prostate cancer (PCa) is the most common cancer in men and the second leading cause of male cancer‐related death. Gleason score (GS) is the primary driver of PCa risk‐stratification and medical decision‐making, but can only be assessed at present via biopsy under anesthesia. Magnetic resonance imaging (MRI) is a promising non‐invasive method to further characterize PCa, providing additional anatomical and functional information. Meanwhile, the diagnostic power of MRI is limited by qualitative or, at best, semi‐quantitative interpretation criteria, leading to inter‐reader variability.Computer‐aided diagnosis employing quantitative MRI analysis has yielded promising results in non‐invasive prediction of GS. However, convolutional neural networks (CNNs) do not implicitly impose a frame of reference to the objects. Thus, CNNs do not encode the positional information properly, limiting method robustness against simple image variations such as flipping, scaling, or rotation. Capsule network (CapsNet) has been proposed to address this limitation and achieves promising results in this domain. In this study, we develop a 3D Efficient CapsNet to stratify GS‐derived PCa risk using T2‐weighted (T2W) MRI images.In our method, we used 3D CNN modules to extract spatial features and primary capsule layers to encode vector features. We then propose to integrate fully‐connected capsule layers (FC Caps) to create a deeper hierarchy for PCa grading prediction. FC Caps comprises a secondary capsule layer which routes active primary capsules and a final capsule layer which outputs PCa risk. To account for data imbalance, we propose a novel dynamic weighted margin loss. We evaluate our method on a public PCa T2W MRI dataset from the Cancer Imaging Archive containing data from 976 patients.Two groups of experiments were performed: (1) we first identified high‐risk disease by classifying low + medium risk versus high risk; (2) we then stratified disease in one‐versus‐one fashion: low versus high risk, medium versus high risk, and low versus medium risk. Five‐fold cross validation was performed. Our model achieved an area under receiver operating characteristic curve (AUC) of 0.83 and 0.64 F1‐score for low versus high grade, 0.79 AUC and 0.75 F1‐score for low + medium versus high grade, 0.75 AUC and 0.69 F1‐score for medium versus high grade and 0.59 AUC and 0.57 F1‐score for low versus medium grade. Our method outperformed state‐of‐the‐art radiomics‐based classification and deep learning methods with the highest metrics for each experiment. Our divide‐and‐conquer strategy achieved weighted Cohen's Kappa score of 0.41, suggesting moderate agreement with ground truth PCa risks.In this study, we proposed a novel 3D Efficient CapsNet for PCa risk stratification and demonstrated its feasibility. This developed tool provided a non‐invasive approach to assess PCa risk from T2W MR images, which might have potential to personalize the treatment of PCa and reduce the number of unnecessary biopsies. [ABSTRACT FROM AUTHOR]

As rural decline sweeps the world and draws public attention, it becomes necessary to consider the relationship between urbanization and rural development. The paper investigates this topic in China for the period 1989–2018. The research results find positive contribution of urbanization to rural economy in the research period but with a decreasing tendency. Compared to less developed areas, rural economy of developed regions has become less dependent on cities and can flourish in a larger context with the support of modern transportation and telecommunication technologies. However, those peripheral rural areas tend to face continuous and large‐scale rural–urban migration which has aggravated rural decline. Rural economic growth helps to decrease rural outmigration and people will stay in their hometown with available job opportunities to raise their families and maintain livelihood. The paper proposes balance‐friendly urbanization structure and diversified rural economy to improve rural resilience to meet the challenge of rural decline. [ABSTRACT FROM AUTHOR]

Despite the remarkable progress of perovskite solar cells (PSCs), challenges remain in terms of finding effective and viable strategies to enhance their long‐term stability while maintaining high efficiency. In this study, a new insulating and hydrophobic fluorinated polyimide (FPI: 6FDA‐6FAPB) was used as the interface layer between the perovskite layer and the hole transport layer (HTL) in PSCs. The functional groups of FPI play a pivotal role in passivating interface defects within the device. Due to its high work function, FPI demonstrates field‐effect passivation (FEP) capabilities as an interface layer, effectively mitigating non‐radiative recombination at the interface. Notably, the FPI insulating interface layer does not impede carrier transmission at the interface, which is attributed to the presence of hole tunneling effects. The optimized PSCs achieve an outstanding power conversion efficiency (PCE) of 24.61 % and demonstrate excellent stability, showcasing the efficacy of FPI in enhancing device performance and reliability. [ABSTRACT FROM AUTHOR]

Despite the remarkable progress of perovskite solar cells (PSCs), challenges remain in terms of finding effective and viable strategies to enhance their long‐term stability while maintaining high efficiency. In this study, a new insulating and hydrophobic fluorinated polyimide (FPI: 6FDA‐6FAPB) was used as the interface layer between the perovskite layer and the hole transport layer (HTL) in PSCs. The functional groups of FPI play a pivotal role in passivating interface defects within the device. Due to its high work function, FPI demonstrates field‐effect passivation (FEP) capabilities as an interface layer, effectively mitigating non‐radiative recombination at the interface. Notably, the FPI insulating interface layer does not impede carrier transmission at the interface, which is attributed to the presence of hole tunneling effects. The optimized PSCs achieve an outstanding power conversion efficiency (PCE) of 24.61 % and demonstrate excellent stability, showcasing the efficacy of FPI in enhancing device performance and reliability. [ABSTRACT FROM AUTHOR]

The occurrence of peritendinous adhesion, which hampers the quality and function of the healed tendon, is strongly linked to oxidative stress, inflammatory, and infection that occur after surgery. Tendon damage and repair provide a considerable obstacle for regenerative medicine owing to the absence of patches that possess comprehensive functionality, including self‐healing capacity, anti‐inflammatory and anti‐bacterial properties, as well as tissue repair guidance. A dual dynamic crosslinked network is created by coordination bonds between catechol groups in protocatechuic aldehyde (PA) and Fe3+, as well as a dynamic Schiff base reaction between amino groups in hyaluronic acid‐adipic acid dihydrazide (HA‐ADH) and aldehyde groups in PA. The HA‐ADH@PA/Fe hydrogel exhibits self‐healing ability, tissue adhesion, anti‐bacterial activity, regulation of macrophage polarization via the NF‐κB signaling, oxidative stress elimination, and anti‐inflammation. In addition, a dual‐layer Janus patch is created, taking inspiration from the anatomy and disease progression of tendon adhesion. The inner layer of the patch, which is in direct contact with the operated tendon, is a multifunctional HA‐ADH@PA/Fe hydrogel, encircled further by a poly(ɛ‐caprolactone) (PCL) electrospinning membrane outer layer facing the surrounding tissue. The PCL@HA‐ADH@PA/Fe hydrogel patch reduced tendon adhesion and supported tissue regeneration by stimulating macrophages polarization into an anti‐inflammatory phenotype and resolving both local and systemic inflammation. This research showcased the PCL@HA‐ADH@PA/Fe hydrogel patch as an alternative therapeutic method for preventing the development of adhesions around tendons. [ABSTRACT FROM AUTHOR]

Researchers have demonstrated that dialogue‐based intelligent tutoring systems (ITS) can be effective in assisting students in learning. However, little research has attempted to explore the necessity of equipping dialogue‐based ITS with one of the most important capabilities of human tutors, that is, maintaining polite interactions with students, which is essential to provide students with a pleasant learning experience. In this study, we examined the role of politeness by analysing a large‐scale real‐world dataset consisting of over 14K online human–human tutorial dialogues. Specifically, we employed linguistic theories of politeness to characterise the politeness levels of tutor–student‐generated utterances, investigated the correlation between the politeness levels of tutors' utterances and students' problem‐solving performance and quantified the power of politeness in predicting students' problem‐solving performance by applying Gradient Tree Boosting. The study results showed that: (i) in the effective tutorial sessions (ie, sessions in which students successfully solved problems), tutors tended to be very polite at the start of a tutorial session and become more direct to guide students as the session progressed; (ii) students with better performance in solving problems tended to be more polite at the beginning and the end of a tutorial session than their counterparts who failed to solve problems; (iii) the correlation between tutors' polite expressions and students' performance was not evident in non‐instructional communication; and (iv) politeness alone cannot adequately reveal students' problem‐solving performance, and thus other factors (eg, sentiment contained in utterances) should also be taken into account. Practitioner notesWhat is already known about this topic Human–human tutoring is acknowledged as an effective instructional method.Polite expression can help strengthen the relationship between tutors and students.Polite expression can promote students' learning achievements in many educational contexts.What this paper adds By considering the students' prior progress on a problem‐based learning task, we demonstrated the extent to which tutors and students display politeness in tutoring dialogues.Tutors' polite expressions might not correlate with students' problem‐solving performance in online human–human tutoring dialogues.Politeness alone was insufficient to predict the students' performance.Implications for practice Tutors might consider using words with positive sentiment values to express politeness to students with prior progress, which might encourage those students to make a further effort.The polite strategy of expressing indirect requests could help tutors mitigate the sense of directness, but this strategy should be carefully used in delivering instructional hints, especially for students without prior progress.To better assist students without prior progress, tutors might consider using more direct expression to explicitly guide students. [ABSTRACT FROM AUTHOR]

This paper examines the roles of physical capital, human capital, and social capital in China's economic growth during the reform period 1981-2010. Empirical estimation confirms that physical capital and human capital contribute to the economic growth, probably due to the capital accumulation and the improvement of labor productivity. The impact of social capital turns from being insignificant in the 1980s and the 1990s to be positive in the 2000s, suggesting its rising importance in recent decades. A declining role of physical capital in the economic growth in China from 1990s to 2000s is also found. The findings hold for several additional robustness checks, including focusing on longer term determinants of the economic growth, subregional analysis, and endogeneity. Furthermore, the foreign direct investment inflows and adjustment of economic ownership structure are also important for economic growth in China. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper introduces a new way of decomposing regional inequality. It divides the Beijing-Tianjin-Hebei metropolitan region into three sets of districts in terms of the urban-rural resource flows: urban, peri-urban, and peripheral areas. Unlike the administrative divisions, these three sets of districts show how resource flows and agglomerates at the regional level. The paper decomposes regional inequality according to the three sets of districts. The paper's findings show that regional inequality decreased between 1990 and 1994, after which it remained steady. The study, for the first time, brings peri-urban areas into a regional decomposition analysis, and contributes to the understanding of urban-rural resource flows and inequality changes at the regional level. [ABSTRACT FROM AUTHOR]

Extracting hot‐carriers before they relax back to the band edge will reduce thermal dissipation above the bandgap, which is one of the primary sources of efficiency loss in perovskite solar cells (PSCs). It requires slow cooling of hot‐carriers together with the efficient extraction of hot‐carriers. Here, a novel interface engineering is demonstrated by embedding radical‐containing nanographene (r‐NG●) between perovskite and poly[bis(4‐phenyl)(2,4‐dimethoxyphenyl)‐amine] (PTOAA) to harvest this excess energy. This strategy accelerates the extraction rate of the hot‐hole (3 times that of control at 400 K) by augmenting the relaxation channel, which is related to the “quasi‐SOMO” energy state of r‐NG●. Nonadiabatic molecular dynamics calculation further revealed that radical character promotes the rotation of the cation in perovskite, which contributes to generating strong nonadiabatic couplings and multiple phonon modes. In addition, the band bending effect of buried perovskite and improved conductivity of PTOAA also facilitate exciton dissociation and hole collection efficiency (97.5%). Consequently, the resultant r‐NG● decorated PSCs delivered an impressive efficiency of 24.20%, along with better thermal and humidity stability. Moreover, it can maintain 93% of its initial efficiency after 300 hours of illumination. [ABSTRACT FROM AUTHOR]

Background and purpose: Magnetic resonance imaging (MRI)‐based synthetic computed tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for CT simulation and error‐prone image registration, ultimately reducing patient radiation dose and setup uncertainty. In this work, we propose a MRI‐to‐CT transformer‐based improved denoising diffusion probabilistic model (MC‐IDDPM) to translate MRI into high‐quality sCT to facilitate radiation treatment planning. Methods: MC‐IDDPM implements diffusion processes with a shifted‐window transformer network to generate sCT from MRI. The proposed model consists of two processes: a forward process, which involves adding Gaussian noise to real CT scans to create noisy images, and a reverse process, in which a shifted‐window transformer V‐net (Swin‐Vnet) denoises the noisy CT scans conditioned on the MRI from the same patient to produce noise‐free CT scans. With an optimally trained Swin‐Vnet, the reverse diffusion process was used to generate noise‐free sCT scans matching MRI anatomy. We evaluated the proposed method by generating sCT from MRI on an institutional brain dataset and an institutional prostate dataset. Quantitative evaluations were conducted using several metrics, including Mean Absolute Error (MAE), Peak Signal‐to‐Noise Ratio (PSNR), Multi‐scale Structure Similarity Index (SSIM), and Normalized Cross Correlation (NCC). Dosimetry analyses were also performed, including comparisons of mean dose and target dose coverages for 95% and 99%. Results: MC‐IDDPM generated brain sCTs with state‐of‐the‐art quantitative results with MAE 48.825 ± 21.491 HU, PSNR 26.491 ± 2.814 dB, SSIM 0.947 ± 0.032, and NCC 0.976 ± 0.019. For the prostate dataset: MAE 55.124 ± 9.414 HU, PSNR 28.708 ± 2.112 dB, SSIM 0.878 ± 0.040, and NCC 0.940 ± 0.039. MC‐IDDPM demonstrates a statistically significant improvement (with p < 0.05) in most metrics when compared to competing networks, for both brain and prostate synthetic CT. Dosimetry analyses indicated that the target dose coverage differences by using CT and sCT were within ± 0.34%. Conclusions: We have developed and validated a novel approach for generating CT images from routine MRIs using a transformer‐based improved DDPM. This model effectively captures the complex relationship between CT and MRI images, allowing for robust and high‐quality synthetic CT images to be generated in a matter of minutes. This approach has the potential to greatly simplify the treatment planning process for radiation therapy by eliminating the need for additional CT scans, reducing the amount of time patients spend in treatment planning, and enhancing the accuracy of treatment delivery. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a prevalent degenerative disease of the joint, featured by articular cartilage destruction and subchondral bone marrow lesions. Articular cartilage and subchondral bone constitute an osteochondral unit that guarantees joint homeostasis. During OA initiation, activated osteoclasts in subchondral bone ultimately result in impaired capacities of the subchondral bone in response to mechanical stress, followed by the degradation of overlying articular cartilage. Thus, targeting osteoclasts could be a potential therapeutic option for treating OA. Here, we observed that farnesoid X receptor (FXR) expression and osteoclast fusion and activity in subchondral bone were concomitantly changed during early‐stage OA in the OA mouse model established by anterior cruciate ligament transection (ACLT). Then, we explored the therapeutic effects of FXR agonist GW4064 on the osteochondral pathologies in ACLT mice. We showed that GW4064 obviously ameliorated subchondral bone deterioration, associated with reduction in tartrate‐resistant acid phosphatase (TRAP) positive multinuclear osteoclast number, as well as articular cartilage degradation, which were blocked by the treatment with FXR antagonist Guggulsterone. Mechanistically, GW4064 impeded osteoclastogenesis through inhibiting subchondral bone osteoclast fusion via suppressing c‐Jun N‐terminal kinase (JNK) 1/2/nuclear factor of activated T‐cells 1 (NFATc1) pathway. Taken together, our results present evidence for the protective effects of GW4064 against OA by blunting osteoclast‐mediated aberrant subchondral bone loss and subsequent cartilage deterioration. Therefore, GW4064 demonstrates the potential as an alternative therapeutic option against OA for further drug development. [ABSTRACT FROM AUTHOR]

Effective collaboration and teamwork skills are critical in high‐risk sectors, as deficiencies in these areas can result in injuries and risk of death. To foster the growth of these vital skills, immersive learning spaces have been created to simulate real‐world scenarios, enabling students to safely improve their teamwork abilities. In such learning environments, multiple dialogue segments can occur concurrently as students independently organise themselves to tackle tasks in parallel across diverse spatial locations. This complex situation creates challenges for educators in assessing teamwork and for students in reflecting on their performance, especially considering the importance of effective communication in embodied teamwork. To address this, we propose an automated approach for generating teamwork analytics based on spatial and speech data. We illustrate this approach within a dynamic, immersive healthcare learning environment centred on embodied teamwork. Moreover, we evaluated whether the automated approach can produce transcriptions and epistemic networks of spatially distributed dialogue segments with a quality comparable to those generated manually for research objectives. This paper makes two key contributions: (1) it proposes an approach that integrates automated speech recognition and natural language processing techniques to automate the transcription and coding of team communication and generate analytics; and (2) it provides analyses of the errors in outputs generated by those techniques, offering insights for researchers and practitioners involved in the design of similar systems.Practitioner notesWhat is currently known about this topic Immersive learning environments simulate real‐world situations, helping students improve their teamwork skills.In these settings, students can have multiple simultaneous conversations while working together on tasks at different physical locations.The dynamic nature of these interactions makes it hard for teachers to assess teamwork and communication and for students to reflect on their performance.What this paper adds We propose a method that employs multimodal learning analytics for automatically generating teamwork‐related insights into the content of student conversations.This data processing method allows for automatically transcribing and coding spatially distributed dialogue segments generated from students working in teams in an immersive learning environment and enables downstream analysis.This approach uses spatial analytics, natural language processing and automated speech recognition techniques.Implications for practitioners Automated coding of dialogue segments among team members can help create analytical tools to assist in evaluating and reflecting on teamwork.By analysing spatial and speech data, it is possible to apply learning analytics advancements to support teaching and learning in fast‐paced physical learning spaces where students can freely engage with one another. [ABSTRACT FROM AUTHOR]

Microbiologically influenced corrosion (MIC) caused by sulfate‐reducing bacteria (SRB) is a major threat to buried pipelines. The crevices beneath disbonded coatings provide the environment for the survival and growth of SRB, accelerating the attachment of SRB and significantly reducing the effectiveness of buried pipelines. In this work, the influence of initial pH values (6.4, 8.0) and SRB concentrations (2.0 × 101, 4.5 × 102, 2.5 × 103 cells/mL) were investigated on the behaviors of L415 carbon steel. The results indicated that the overall uniform corrosion rate of L415 carbon steel decreased while the maximum pitting corrosion rate exhibited an increasing trend with the increasing of initial concentration of SRB. In comparison to the pH 6.4 environment, the overall risk of pitting corrosion in pH 8.0 environment was reduced due to the biomineralization of SRB, enhancing the protection of metal materials. [ABSTRACT FROM AUTHOR]

Ultraviolet‐induced degradation has emerged as a critical stability concern impeding the widespread adoption of perovskite solar cells (PSCs), particularly in the context of phase‐unstable wide‐band gap perovskite films. This study introduces a novel approach by employing a fully aromatic carbazole‐based self‐assembled monolayer, denoted as (4‐(3,6‐dimethoxy‐9H‐carbazol‐9‐yl)phenyl)phosphonic acid (MeO‐PhPACz), as a hole‐selective layer (HSL) in inverted wide‐band gap PSCs. Incorporating a conjugated linker plays a pivotal role in promoting the formation of a dense and highly ordered HSL on substrates, facilitating subsequent perovskite interfacial interactions, and fostering the growth of uniform perovskite films. The high‐quality film could effectively suppress interfacial non‐radiative recombination, improving hole extraction/transport efficiency. Through these advancements, the optimized wide‐band gap PSCs, featuring a band gap of 1.68 eV, attain an impressive power conversion efficiency (PCE) of 21.10 %. Remarkably, MeO‐PhPACz demonstrates inherent UV resistance and heightened UV absorption capabilities, substantially improving UV resistance for the targeted PSCs. This characteristic holds significance for the feasibility of large‐scale outdoor applications. [ABSTRACT FROM AUTHOR]

Ultraviolet‐induced degradation has emerged as a critical stability concern impeding the widespread adoption of perovskite solar cells (PSCs), particularly in the context of phase‐unstable wide‐band gap perovskite films. This study introduces a novel approach by employing a fully aromatic carbazole‐based self‐assembled monolayer, denoted as (4‐(3,6‐dimethoxy‐9H‐carbazol‐9‐yl)phenyl)phosphonic acid (MeO‐PhPACz), as a hole‐selective layer (HSL) in inverted wide‐band gap PSCs. Incorporating a conjugated linker plays a pivotal role in promoting the formation of a dense and highly ordered HSL on substrates, facilitating subsequent perovskite interfacial interactions, and fostering the growth of uniform perovskite films. The high‐quality film could effectively suppress interfacial non‐radiative recombination, improving hole extraction/transport efficiency. Through these advancements, the optimized wide‐band gap PSCs, featuring a band gap of 1.68 eV, attain an impressive power conversion efficiency (PCE) of 21.10 %. Remarkably, MeO‐PhPACz demonstrates inherent UV resistance and heightened UV absorption capabilities, substantially improving UV resistance for the targeted PSCs. This characteristic holds significance for the feasibility of large‐scale outdoor applications. [ABSTRACT FROM AUTHOR]

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are concerns regarding the practicality and ethicality of these innovations. Such concerns may hinder future research and the adoption of LLMs‐based innovations in authentic educational contexts. To address this, we conducted a systematic scoping review of 118 peer‐reviewed papers published since 2017 to pinpoint the current state of research on using LLMs to automate and support educational tasks. The findings revealed 53 use cases for LLMs in automating education tasks, categorised into nine main categories: profiling/labelling, detection, grading, teaching support, prediction, knowledge representation, feedback, content generation, and recommendation. Additionally, we also identified several practical and ethical challenges, including low technological readiness, lack of replicability and transparency and insufficient privacy and beneficence considerations. The findings were summarised into three recommendations for future studies, including updating existing innovations with state‐of‐the‐art models (eg, GPT‐3/4), embracing the initiative of open‐sourcing models/systems, and adopting a human‐centred approach throughout the developmental process. As the intersection of AI and education is continuously evolving, the findings of this study can serve as an essential reference point for researchers, allowing them to leverage the strengths, learn from the limitations, and uncover potential research opportunities enabled by ChatGPT and other generative AI models. Practitioner notesWhat is currently known about this topic Generating and analysing text‐based content are time‐consuming and laborious tasks.Large language models are capable of efficiently analysing an unprecedented amount of textual content and completing complex natural language processing and generation tasks.Large language models have been increasingly used to develop educational technologies that aim to automate the generation and analysis of textual content, such as automated question generation and essay scoring.What this paper adds A comprehensive list of different educational tasks that could potentially benefit from LLMs‐based innovations through automation.A structured assessment of the practicality and ethicality of existing LLMs‐based innovations from seven important aspects using established frameworks.Three recommendations that could potentially support future studies to develop LLMs‐based innovations that are practical and ethical to implement in authentic educational contexts.Implications for practice and/or policy Updating existing innovations with state‐of‐the‐art models may further reduce the amount of manual effort required for adapting existing models to different educational tasks.The reporting standards of empirical research that aims to develop educational technologies using large language models need to be improved.Adopting a human‐centred approach throughout the developmental process could contribute to resolving the practical and ethical challenges of large language models in education. [ABSTRACT FROM AUTHOR]

Objectives: Cardiac Ca2+ signalling plays an essential role in regulating excitation‐contraction coupling and cardiac remodelling. However, the response of cardiomyocytes to simulated microgravity and hypergravity and the effects on Ca2+ signalling remain unknown. Here, we elucidate the mechanisms underlying the proliferation and remodelling of HL‐1 cardiomyocytes subjected to rotation‐simulated microgravity and 4G hypergravity. Materials and Methods: The cardiomyocyte cell line HL‐1 was used in this study. A clinostat and centrifuge were used to study the effects of microgravity and hypergravity, respectively, on cells. Calcium signalling was detected with laser scanning confocal microscopy. Protein and mRNA levels were detected by Western blotting and real‐time PCR, respectively. Wheat germ agglutinin (WGA) staining was used to analyse cell size. Results: Our data showed that spontaneous calcium oscillations and cytosolic calcium concentration are both increased in HL‐1 cells after simulated microgravity and 4G hypergravity. Increased cytosolic calcium leads to activation of calmodulin‐dependent protein kinase II/histone deacetylase 4 (CaMKII/HDAC4) signalling and upregulation of the foetal genes ANP and BNP, indicating cardiac remodelling. WGA staining indicated that cell size was decreased following rotation‐simulated microgravity and increased following 4G hypergravity. Moreover, HL‐1 cell proliferation was increased significantly under hypergravity but not rotation‐simulated microgravity. Conclusions: Our study demonstrates for the first time that Ca2+/CaMKII/HDAC4 signalling plays a pivotal role in myocardial remodelling under rotation‐simulated microgravity and hypergravity. [ABSTRACT FROM AUTHOR]

The objective of this paper is to propose a hierarchical topic evolution model ( HTEM) that can organize time-varying topics in a hierarchy and discover their evolutions with multiple timescales. In the proposed HTEM, topics near the root of the hierarchy are more abstract and also evolve in the longer timescales than those near the leaves. To achieve this goal, the distance-dependent Chinese restaurant process (dd CRP) is extended to a new nested process that is able to simultaneously model the dependencies among data and the relationship between clusters. The HTEM is proposed based on the new process for time-stamped documents, in which the timestamp is utilized to measure the dependencies among documents. Moreover, an efficient Gibbs sampler is developed for the proposed HTEM. Our experimental results on two popular real-world data sets verify that the proposed HTEM can capture coherent topics and discover their hierarchical evolutions. It also outperforms the baseline model in terms of likelihood on held-out data. [ABSTRACT FROM AUTHOR]