The impact of solar activity on the 2015/16 El Niño event

Recent SST and atmospheric circulation anomaly data suggest that the 2015/16 El Niño event is quickly decaying. Some researchers have predicted a forthcoming La Niña event in late summer or early fall 2016. From the perspective of the modulation of tropical SST by solar activity, the authors studied the evolution of the 2015/16 El Niño event, which occurred right after the 2014 solar peak year. Based on statistical and composite analysis, a significant positive correlation was found between sunspot number index and El Niño Modoki index, with a lag of two years. A clear evolution of El Niño Modoki events was found within 1–3 years following each solar peak year during the past 126 years, suggesting that anomalously strong solar activity during solar peak periods favors the triggering of an El Niño Modoki event. The patterns of seasonal mean SST and wind anomalies since 2014 are more like a mixture of two types of El Niño (i.e. eastern Pacific El Niño and El Niño Modoki), which is similar to the pattern modulated by solar activity during the years following a solar peak. Therefore, the El Niño Modoki component in the 2015/16 El Niño event may be a consequence of solar activity, which probably will not decay as quickly as the eastern Pacific El Niño component. The positive SST anomaly will probably sustain in the central equatorial Pacific (around the dateline) and the northeastern Pacific along the coast of North America, with a low-intensity level, during the second half of 2016

The possible impact of solar activity on the summer temperature distribution over Eurasia

The effect of solar activity on the regional temperature in winter has been widely discussed. However, whether the summer temperature of land in the northern hemisphere is sensitive to solar activity remains to be further investigated. In this study, the empirical orthogonal function (EOF) analysis, spectrum analysis, and correlation analysis are employed to reveal the possible link between the summer temperature distribution over Eurasian land (0–180°E and 20°N−80°N) and solar activity. The results show that the corresponding time series of the second pattern significantly exhibits an 11-year solar periodicity. Its tripolar temperature distribution is similar to the correlation maps between the temperature and sunspot number (SSN). Particularly, Central Asia (50°E−90°E and 30°N−60°N) is the key response region over Eurasia. The temperature of Central Asia shows a weak but significant negative correlation with SSN. Further analysis of atmospheric circulation indicates that the solar-induced cyclonic and negative geopotential height anomalies in Central Asia weaken the high-pressure ridge on the southwest side and strengthen northwesterly winds. At the same time, with the increase in the cloud cover and the decrease of shortwave radiation, the temperature is lowered. Due to the impact of solar activity, the upper atmosphere over Eurasia forms a wave train-like structure, resulting in a tripolar temperature distribution pattern. On the other hand, the 21-year sliding correlation results suggest that the connection between solar activity and the temperature in Central Asia was strong and decadal stable until 1980. Whereas the temperature and atmospheric circulations in high latitudes become more sensitive to solar activity after 1980. Anyway, solar activity still can be considered a non-negligible factor in the prediction of the summer temperature in Eurasia

TANGO: Time-Reversal Latent GraphODE for Multi-Agent Dynamical Systems

Learning complex multi-agent system dynamics from data is crucial across many domains, such as in physical simulations and material modeling. Extended from purely data-driven approaches, existing physics-informed approaches such as Hamiltonian Neural Network strictly follow energy conservation law to introduce inductive bias, making their learning more sample efficiently. However, many real-world systems do not strictly conserve energy, such as spring systems with frictions. Recognizing this, we turn our attention to a broader physical principle: Time-Reversal Symmetry, which depicts that the dynamics of a system shall remain invariant when traversed back over time. It still helps to preserve energies for conservative systems and in the meanwhile, serves as a strong inductive bias for non-conservative, reversible systems. To inject such inductive bias, in this paper, we propose a simple-yet-effective self-supervised regularization term as a soft constraint that aligns the forward and backward trajectories predicted by a continuous graph neural network-based ordinary differential equation (GraphODE). It effectively imposes time-reversal symmetry to enable more accurate model predictions across a wider range of dynamical systems under classical mechanics. In addition, we further provide theoretical analysis to show that our regularization essentially minimizes higher-order Taylor expansion terms during the ODE integration steps, which enables our model to be more noise-tolerant and even applicable to irreversible systems. Experimental results on a variety of physical systems demonstrate the effectiveness of our proposed method. Particularly, it achieves an MSE improvement of 11.5 % on a challenging chaotic triple-pendulum systems

Comparison of the Biochemical Composition and Nutritional Quality Between Diploid and Triploid Hong Kong Oysters, Crassostrea hongkongensis

This study is the first systematic comparison of the biochemical composition and nutritional quality between diploid and triploid Hong Kong oysters, Crassostrea hongkongensis. Results showed that in the reproductive season, the glycogen content in five tissues (gill, mantle, adductor muscle, labial palps and gonad) was significantly higher (P < 0.05) in triploids than in diploids, with odds ratios (ORs) of 96.26, 60.17, 72.59, 53.56, and 128.52%, respectively. In the non-reproductive phase, significant differences in glycogen content (P < 0.05) between diploid and triploid oysters existed only in gill and gonad. In both diploid and triploid Hong Kong oysters, quantitative real-time PCR analysis of the glycogen synthesis gene (ChGS) and glycogen phosphorylase gene (ChGP) showed that the gene expression patterns matched the pattern of variation in glycogen content. Moreover, in both the reproductive and the non-reproductive phases, triploid Hong Kong oysters had a well balance of essential amino acids and were thus a well source of high-quality protein. Surprisingly, in both phases, significantly higher (P < 0.05) percentages of four essential fatty acids (α-linolenic acid, linoleic acid, eicosapentaenoic acid, and docosahexaenoic acid) were observed in triploids than in diploids. Additionally, the ratio of n-3/n-6 polyunsaturated fatty acids (PUFAs) was much higher in triploids than that in diploids. Variations in Biochemical composition were consistent with the relative expression of the citrate synthase gene (ChCS) and the α-ketoglutarate dehydrogenase gene (ChKD), which are key enzyme genes of the tricarboxylic acid cycle. Overall, the triploid Hong Kong oyster has a better nutritional value and taste than the diploid in terms of glycogen content, protein quality and fatty acid content

Analysis of in situ Transcriptomes Reveals Divergent Adaptive Response to Hyper- and Hypo-Salinity in the Hong Kong Oyster, Crassostrea hongkongensis

Crassostrea hongkongensis, a commercially valuable aquaculture species dwelling in estuaries along the coast of the South China Sea, is remarkable for its eurysalinity traits that enable its successful colonization of diverse osmotic niches ranging from near freshwater to seawater. In order to elucidate how this oyster copes with coastal waters with immense salinity differences, we performed in situ transcriptomic analysis (RNA-seq) to characterize the global expression patterns of oysters distributed across naturally formed salinity gradients in Zhenhai Bay along the northern coast of the South China Sea. Principal component analysis reveals distinct expression profiles of oysters living in the extreme conditions of hypo-salinity and hyper-salinity. Compared with the situation of optimal salinity for oyster growth, hypo-salinity mainly regulated expression of genes involved in FoxO and oxytocin signaling, tight junction and several immune pathways, while hyper-salinity altered gene expression implicated in amino acid metabolism, AMPK and PI3K-AKt signaling pathways, demonstrating the complexity and plasticity of transcriptomic expression underpinning oyster eurysalinity. Furthermore, the expression patterns of several genes correlated with salinity gradients reveals the fine-tuned coordination of molecular networks necessary for adaptive homeostasis in C. hongkongensis. In conclusion, a striking capacity and distinct patterns of transcriptomic expression contribute to eurysalinity adaptation in C. hongkongensis, which provides new mechanistic insights into the adaptive plasticity and resilience of marine mollusks

DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation

Heterogeneous information network has been widely used to alleviate sparsity and cold start problems in recommender systems since it can model rich context information in user-item interactions. Graph neural network is able to encode this rich context information through propagation on the graph. However, existing heterogeneous graph neural networks neglect entanglement of the latent factors stemming from different aspects. Moreover, meta paths in existing approaches are simplified as connecting paths or side information between node pairs, overlooking the rich semantic information in the paths. In this paper, we propose a novel disentangled heterogeneous graph attention network DisenHAN for top-$N$ recommendation, which learns disentangled user/item representations from different aspects in a heterogeneous information network. In particular, we use meta relations to decompose high-order connectivity between node pairs and propose a disentangled embedding propagation layer which can iteratively identify the major aspect of meta relations. Our model aggregates corresponding aspect features from each meta relation for the target user/item. With different layers of embedding propagation, DisenHAN is able to explicitly capture the collaborative filtering effect semantically. Extensive experiments on three real-world datasets show that DisenHAN consistently outperforms state-of-the-art approaches. We further demonstrate the effectiveness and interpretability of the learned disentangled representations via insightful case studies and visualization.Comment: Accepted at CIKM202

Hippo dictates signaling for cellular homeostasis and immune defense in Crassostrea hongkongensis hemocytes

IntroductionThe Hippo signaling pathway is an evolutionarily conserved signaling cascade that plays a crucial role in regulating cell proliferation, differentiation, and apoptosis. It has been shown to be a key regulator of cell fate and cellular homeostasis in various immune processes. Despite its well-established functions in vertebrate immunity, its roles in marine invertebrate immunity remain poorly understood. Therefore, our present work provides fresh mechanistic insights into how the Hippo pathway orchestrates hemocytic functions in Crassostrea hongkongensis, with implications for studies on its major forms and modifications in animal evolution.MethodThe complete set of Hippo pathway genes, including SAV1, MOB1, LATS, YAP/TAZ, TEAD, and MST, were identified from the C. hongkongensis genome. Quantitative PCR assays were conducted to examine the mRNA expression levels of these genes in different tissues and the levels of these genes in hemocytes before and after bacterial challenges. The study also examined the crosstalk between the Hippo pathway and other immune pathways, such as the AP-1 and p53-dependent p21 signaling cascades. RNA interference was used to knock down MST and TEAD, and MST is a core orchestrator of non-canonical Hippo signaling, to investigate its impact on phagocytosis and bacterial clearance in hemocytes.ResultThe results demonstrated that members of the Hippo pathway were highly expressed in hemocytes, with their expression levels significantly increasing following bacterial challenges. Crosstalk between the Hippo pathway and other immune pathways triggered hemocytic apoptosis, which functioned similarly to the canonical Mst-Lats-Yap signaling pathway in Drosophila and mammals. Knocking down MST resulted in increased phagocytosis and boosted the efficiency of bacterial clearance in hemocytes, presumably due to mobilized antioxidant transcription by Nrf for maintaining immune homeostasis.DiscussionThis study provides novel insights into the regulatory mechanisms underlying the Hippo pathway in immune responses of C. hongkongensis hemocytes. The study highlights the importance of the Hippo pathway in maintaining immune homeostasis and orchestrating hemocytic functions in oysters. Moreover, this study demonstrates the divergence of the Hippo pathway's roles in marine invertebrate immunity from mammalian observations, indicating the need for further comparative studies across species. These findings have significant implications for future research aimed at elucidating the evolutionary trajectory and functional diversity of the Hippo signaling pathway in animal evolution

Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings

We introduce a novel suite of state-of-the-art bilingual text embedding models that are designed to support English and another target language. These models are capable of processing lengthy text inputs with up to 8192 tokens, making them highly versatile for a range of natural language processing tasks such as text retrieval, clustering, and semantic textual similarity (STS) calculations. By focusing on bilingual models and introducing a unique multi-task learning objective, we have significantly improved the model performance on STS tasks, which outperforms the capabilities of existing multilingual models in both target language understanding and cross-lingual evaluation tasks. Moreover, our bilingual models are more efficient, requiring fewer parameters and less memory due to their smaller vocabulary needs. Furthermore, we have expanded the Massive Text Embedding Benchmark (MTEB) to include benchmarks for German and Spanish embedding models. This integration aims to stimulate further research and advancement in text embedding technologies for these languages

Energy transmission processes in the effectuation chain of solar forcing to the terrestrial atmosphere—a review

The Sun has an obvious quasi-11-year cycle and numerous short-term eruptive activities. There are four processes of energy transmission in the effectuation chain of solar forcing to the climate system: solar energy input into the atmosphere, atmospheric absorption of the input energy, transformation of the absorbed energy into dynamic and thermodynamic responses in the atmosphere, and coupling among all the layers affected by solar forcings. However, the four processes have not been discussed in their entirety. This present paper reviews studies over the last decade on how solar radiation varies during the solar cycle and solar eruptions, and, correspondingly, how the terrestrial atmosphere absorbs the input solar energy